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Oleg K., Software Engineer

Ukraine
Last Updated: 7 Dec 2023

Software Engineer with proficiency in data engineering, specializing in backend development and data processing. Accrued expertise in building and maintaining scalable data systems using technologies such as Scala, Akka, SBT, ScalaTest, Elasticsearch, RabbitMQ, Kubernetes, and cloud platforms like AWS and Google Cloud. Holds a solid foundation in computer science with a Master's degree in Software Engineering, ongoing Ph.D. studies, and advanced certifications. Demonstrates strong proficiency in English, underpinned by international experience. Adept at incorporating CI/CD practices, contributing to all stages of the software development lifecycle. Track record of enhancing querying capabilities through native language text processing and executing complex CI/CD pipelines. Distinguished by technical agility, consistently delivering improvements in processing flows and back-end systems.

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Akka

Akka

Scala

Scala

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Yaroslav M., Scala Software Engineer with Cloud & Data Engineering skills

Ternopil, Ukraine
Last Updated: 4 Jul 2023

- Professional engineer with proven ability to develop efficient solutions for complex problems, including cloud and Data projects; - Microservice architecture expertise Lightbend Reactive Architecture, Infrastructure as Code expertise in AWS CloudFormation, CI/CD (Gitlab, AWS CodePipeline), Cloud expertise - AWS; -Engineer with the ability to develop efficient solutions for complex problems, including cloud projects, AWS Services (Amazon Quicksight, EC2, S3, Glue), Databricks, Kinesis; - API development RESTful, Swagger, GraphQL, API Gateway, Microservice architecture expertise - Commercial experience in IT since 2013; - Lightbend Reactive Architecture, Infrastructure as Code expertise in AWS CloudFormation, CI/CD (Gitlab, AWS CodePipeline); - System level programming, OOP and OOD, functional programming; Stress on profiling and optimizing code, writing reliable code; - System-level programming, OOP and OOD, functional programming; - Profiling and optimizing JVM code; - Experience with product documentation and supporting products; - Upper-intermediate English; - Available ASAP.

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Akka

Akka

Scala

Scala

SQL

SQL

Amazon Web Services (AWS)

Amazon Web Services (AWS)

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Yuriy D., Data Engineer / Data Architect

Ternopil, Ukraine
Last Updated: 4 Jul 2023

- 14+ years of experience in IT; - Data Engineering and Data Architecture Experience - System-level programming, OOP and OOD, functional programming; - Profiling and optimizing code; - Writing reliable code; - Writing product documentation, supporting products; - Team working, team leading; - Strong knowledge in Mathematics and physics (over 30 scientific publications); - Mentoring skills as a senior developer;

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Akka

Akka

Python

Python

C++

C++

Scala

Scala

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Artem, Scala Software Engineer with AWS Cloud

Ternopil, Ukraine
Last Updated: 4 Jul 2023
Akka

Akka

Scala

Scala

Java

Java

Amazon Web Services (AWS)

Amazon Web Services (AWS)

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Mykola V., Data Architect

Ukraine
Last Updated: 4 Jul 2023

- Skillful Data architect with strong expertise in the Hadoop ecosystem (Clouder/Hortonworks Data Platforms), AWS Data services, and more than 15 years of experience delivering software solutions. - Intermediate English - Available ASAP

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Akka

Akka

Apache Spark

Apache Spark

Apache Kafka

Apache Kafka

Apache Hadoop

Apache Hadoop

Scala

Scala   2 yr.

Amazon Web Services (AWS)

Amazon Web Services (AWS)

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Table of Contents

TOP 10 Akka Related Technologies

  • Java

    Java is the most widely used programming language for Akka software development. It provides a robust and reliable platform for building distributed and concurrent applications. With its rich ecosystem and extensive community support, Java offers developers a wide range of libraries and frameworks to enhance their Akka projects.

  • Scala

    Scala is another popular language for Akka development. It combines object-oriented and functional programming paradigms, making it a powerful tool for building highly scalable and fault-tolerant applications using Akka. Scala’s concise syntax and strong type inference system contribute to faster development and easier maintenance of Akka projects.

  • Akka Framework

    Akka is a toolkit and runtime for building highly concurrent, distributed, and fault-tolerant applications on the JVM. It provides actors as a concurrency model, allowing developers to write asynchronous and scalable code easily. Akka’s supervision and fault tolerance mechanisms make it a preferred choice for building reactive and resilient systems.

  • Play Framework

    Play Framework is a web development framework that integrates well with Akka. It follows the reactive programming model and offers built-in support for handling asynchronous operations. Play Framework’s intuitive API and powerful features, such as hot reloading and distributed computing support, make it an excellent choice for building Akka-based web applications.

  • Slick

    Slick is a modern database query and access library for Scala. It integrates seamlessly with Akka and provides a type-safe and efficient way to interact with databases. With its powerful query composition capabilities and support for various database backends, Slick simplifies data access and manipulation in Akka applications.

  • Apache Kafka

    Apache Kafka is a distributed event streaming platform that is widely used in Akka-based systems for building scalable and fault-tolerant message-driven architectures. Kafka’s high throughput, fault tolerance, and support for real-time data processing make it an ideal choice for building reactive and event-driven applications with Akka.

  • Docker

    Docker is a containerization platform that simplifies the deployment and management of Akka applications. With Docker, developers can package their Akka applications along with their dependencies into lightweight and portable containers. This enables easy scalability, versioning, and isolation of Akka services, making Docker an essential tool for Akka software development.

Cases when Akka does not work

  1. Akka may not be suitable for small-scale applications that do not require high concurrency and fault-tolerance. It is designed to handle complex distributed systems, so using Akka in simple applications may introduce unnecessary complexity and overhead.
  2. If your application has strict real-time requirements, Akka may not be the best choice. While Akka provides high-performance message passing, it still incurs some overhead due to its actor model. In scenarios where microseconds matter, a lower-level framework or language might be more suitable.
  3. If your application heavily relies on blocking I/O operations, such as synchronous database queries or file operations, Akka may not be the ideal solution. Akka is built around the concept of non-blocking, asynchronous communication, and blocking operations can potentially introduce performance bottlenecks and reduce the benefits of using Akka.
  4. In cases where your application requires strong consistency guarantees and ACID transactions, Akka’s default event-driven, eventually consistent model may not be the best fit. Akka is designed to handle eventual consistency and is more suited for systems that prioritize availability and partition tolerance over strong consistency.
  5. If your development team lacks experience with asynchronous programming and the actor model, adopting Akka may involve a steep learning curve. Akka’s programming model requires developers to think in terms of message passing and actors, which can be quite different from traditional imperative or object-oriented programming paradigms.
  6. Finally, if your application does not require distribution across multiple nodes or does not have scalability requirements, using Akka may be overkill. Akka shines when it comes to building highly scalable, distributed systems, but if your application can be easily handled by a single server or a simpler framework, the additional complexity introduced by Akka may not be justified.

Let’s consider Difference between Junior, Middle, Senior, Expert/Team Lead developer roles.

Seniority NameYears of experienceResponsibilities and activitiesAverage salary (USD/year)
Junior0-2 yearsAssist with basic coding tasks, bug fixing, and testing. Collaborate with senior developers and learn from them. Contribute to smaller projects under supervision.$50,000 – $70,000
Middle2-5 yearsWrite and maintain code independently. Take ownership of specific features or modules. Collaborate with team members to design and implement solutions. Assist junior developers and provide guidance.$70,000 – $90,000
Senior5-10 yearsLead the development of complex features or projects. Mentor and guide junior and middle developers. Contribute to architectural decisions. Collaborate with cross-functional teams. Ensure code quality and performance optimizations.$90,000 – $120,000
Expert/Team Lead10+ yearsProvide technical leadership and guidance to the team. Define and drive the overall technical strategy. Mentor and coach team members. Collaborate with stakeholders to align business goals with technical solutions. Drive innovation and continuous improvement.$120,000 – $150,000+

How and where is Akka used?

Case NameCase Description
Case 1: Real-time Data StreamingAkka development is widely used for real-time data streaming applications. For example, Akka Streams provides a high-level API for building stream processing applications that can handle large volumes of data in real-time. This is particularly useful in industries such as finance, where real-time data processing is crucial for making informed trading decisions.
Case 2: Distributed ComputingAkka development enables distributed computing by implementing the Actor model, which allows for concurrent and distributed processing. Akka Actors provide a lightweight and scalable way to build distributed systems, making it suitable for applications that require high availability and fault tolerance. For instance, Akka Cluster enables the creation of fault-tolerant clusters of Akka Actors, allowing developers to build resilient distributed applications.
Case 3: IoT (Internet of Things) ApplicationsAkka development is well-suited for building IoT applications due to its support for asynchronous and event-driven programming. IoT devices generate a massive amount of data that needs to be processed and acted upon in real-time. With Akka, developers can easily handle the concurrent processing of IoT data and build reactive systems that can react to events in real-time, making it an ideal choice for IoT applications.
Case 4: Gaming and SimulationsAkka’s actor-based model is highly suitable for building gaming and simulation applications. The concurrent and distributed nature of Akka allows for the creation of complex game worlds and simulations that can be processed in parallel. Akka’s fault-tolerance capabilities also ensure that the game or simulation remains stable even in the presence of failures or high user load.
Case 5: Financial SystemsAkka development is widely used in the finance industry to build high-performance and fault-tolerant systems. Akka’s concurrency model allows for efficient processing of financial transactions and data, ensuring low latency and high throughput. Additionally, Akka’s supervision capabilities enable the system to recover from failures and maintain the integrity of financial operations.
Case 6: TelecommunicationsAkka is often used in telecommunications applications to handle the significant amount of data generated by network devices and services. With Akka Streams, developers can easily process and transform data streams in real-time, enabling efficient monitoring, analysis, and management of telecommunications networks. Akka’s scalability and fault tolerance are particularly valuable in this domain, where high availability is critical.
Case 7: Chat and Messaging ApplicationsAkka’s actor model is well-suited for building chat and messaging applications that require high concurrency and real-time communication. Akka Actors can represent individual chat users, allowing for efficient message handling and scaling. Akka’s fault-tolerance mechanisms ensure that the chat application remains responsive even in the presence of failures, making it a reliable choice for building scalable chat systems.

TOP 14 Tech facts and history of creation and versions about Akka Development

  • Akka is an open-source toolkit and runtime for building highly scalable, concurrent, and distributed applications on the Java Virtual Machine (JVM). It was created in 2009 by Jonas Bonér, Roland Kuhn, and Martin Krasser.
  • Akka is based on the Actor Model, a mathematical model for concurrent computation that provides a higher-level abstraction for handling concurrency compared to traditional thread-based approaches.
  • One of the key features of Akka is its fault-tolerance mechanism. It allows actors to fail and be automatically restarted by their supervisors, ensuring the overall system remains stable and resilient.
  • Akka provides a distributed programming model, allowing actors to communicate and interact across multiple nodes in a cluster. This enables the development of highly scalable and fault-tolerant applications.
  • In 2013, Akka 2.2 was released, introducing the Cluster module. This module added support for clustering, allowing actors to be distributed across multiple nodes and providing automatic load balancing and failover capabilities.
  • Akka Streams, introduced in 2015 with Akka 2.4, is a powerful stream processing library that enables the processing of large streams of data with backpressure support.
  • Akka Persistence, introduced in 2015 with Akka 2.4, provides a framework for building event-sourced applications, where the state of an application is derived by applying a sequence of events.
  • Akka Typed, introduced in 2017 with Akka 2.5, brings a more type-safe API to Akka, leveraging the power of Scala’s type system to prevent common runtime errors and provide better tooling support.
  • Akka HTTP, introduced in 2016, is a module that provides a full-featured, high-performance HTTP server and client based on Akka actors and streams.
  • Akka Cluster Sharding, introduced in 2017 with Akka 2.5, is a module that simplifies the distribution and management of stateful actors across a cluster, enabling scalable and fault-tolerant solutions.
  • Akka gRPC, introduced in 2017, combines the power of Akka Streams and Google’s gRPC framework to provide a high-performance, asynchronous, and non-blocking way of building distributed systems.
  • Akka Typed Cluster, introduced in 2019 with Akka 2.6, extends the type-safe API of Akka Typed to support distributed actors in a clustered environment, making it easier to build resilient and scalable distributed applications.
  • Akka Serverless, introduced in 2020, is a cloud-native runtime for stateful serverless applications built on Akka. It provides automatic scaling, fault-tolerance, and event-sourcing capabilities out of the box.
  • Akka has a vibrant and active community, with regular releases and updates. It is widely adopted by companies such as PayPal, LinkedIn, Walmart, and many others for building highly concurrent and distributed systems.
  • Akka is written in Scala but provides APIs for both Scala and Java. This allows developers from different backgrounds to leverage the power of Akka and build scalable applications using their preferred programming language.

Pros & cons of Akka

8 Pros of Akka

  • Scalability: Akka is designed to handle large-scale distributed applications, allowing developers to easily scale their systems horizontally by adding more nodes.
  • Concurrency: Akka provides a highly efficient model for managing concurrency, making it easier to write concurrent and parallel programs without worrying about low-level details.
  • Fault-tolerance: Akka comes with built-in fault-tolerance mechanisms, such as supervisor hierarchies and actor restarts, which enable applications to recover from failures and continue running smoothly.
  • Distributed computing: Akka allows developers to build distributed systems by providing tools for message-based communication between remote actors, making it easier to create fault-tolerant and scalable applications across multiple nodes.
  • Actor model: Akka is based on the actor model, which provides a high-level abstraction for building concurrent and distributed systems. The actor model simplifies the programming model by encapsulating state and behavior within actors, allowing for better modularity and easier testing.
  • Asynchronous processing: Akka promotes asynchronous message passing between actors, which enables efficient utilization of system resources and improves overall system responsiveness.
  • Integration with other technologies: Akka integrates well with other popular technologies such as Akka Streams, Akka HTTP, and Akka Persistence, allowing developers to build end-to-end reactive systems.
  • Community and support: Akka has a large and active community, with extensive documentation, tutorials, and forums available for developers to seek help and share knowledge.

8 Cons of Akka

  • Learning curve: Akka has a steep learning curve, especially for developers who are new to the actor model or distributed systems. It requires a paradigm shift in thinking and understanding of asynchronous programming concepts.
  • Complexity: Building complex systems with Akka can be challenging due to the inherent complexity of distributed systems. Developers need to carefully design and architect their applications to ensure proper fault-tolerance and scalability.
  • Debugging and testing: Debugging and testing distributed systems can be more difficult compared to traditional monolithic applications. Proper tools and techniques need to be used to effectively test and debug Akka applications.
  • Performance overhead: Akka introduces some performance overhead due to the abstractions and mechanisms it provides. While it offers scalability and fault-tolerance benefits, developers need to carefully consider the trade-offs and performance implications of using Akka.
  • Resource management: Managing system resources, such as threads and memory, can be challenging in Akka applications. Developers need to be aware of resource utilization and carefully manage them to avoid bottlenecks and performance issues.
  • Integration complexities: Integrating Akka with existing systems or technologies can sometimes be complex, especially if they are not designed with distributed systems in mind. Proper planning and understanding of integration requirements are crucial.
  • Version compatibility: Upgrading Akka versions can sometimes introduce compatibility issues, especially when there are breaking changes or deprecated features. Developers need to be cautious and plan for smooth upgrades.
  • Monitoring and observability: Monitoring and observability of Akka applications can be more challenging compared to traditional applications. Specialized tools and techniques need to be used to effectively monitor and debug distributed systems.

Hard skills of a Akka Developer

Akka is a powerful and popular toolkit for building highly concurrent, distributed, and fault-tolerant applications in the Java and Scala programming languages. As an Akka developer, you need to possess a range of hard skills to effectively leverage this framework and create robust applications.

Junior

  • Scala or Java Programming: Proficiency in either Scala or Java is essential for developing Akka applications.
  • Akka Basics: Understanding the core concepts of Akka, such as actors, message passing, and supervision, is crucial.
  • Concurrency and Parallelism: Knowledge of concurrent programming principles and experience with multithreading is necessary.
  • RESTful APIs: Familiarity with building and consuming RESTful APIs using frameworks like Akka HTTP.
  • Database Integration: Basic understanding of database concepts and experience with integrating Akka applications with databases.

Middle

  • Akka Streams: Proficiency in working with Akka Streams for building reactive and stream processing applications.
  • Distributed Systems: Experience with designing and implementing distributed systems using Akka Cluster.
  • Testing: Knowledge of testing Akka applications using frameworks like Akka TestKit.
  • Performance Optimization: Ability to optimize the performance of Akka applications through tuning and profiling.
  • Event Sourcing and CQRS: Understanding of event sourcing and command-query responsibility segregation (CQRS) patterns.
  • Monitoring and Logging: Experience with monitoring and logging tools to ensure the health and performance of Akka applications.
  • Message Brokers: Familiarity with message brokers like Apache Kafka for building event-driven architectures.

Senior

  • Cluster Sharding: Proficiency in using Akka Cluster Sharding for building scalable and fault-tolerant systems.
  • Akka Persistence: Experience with Akka Persistence for building applications with event sourcing and persistence.
  • Reactive Streams: Knowledge of the Reactive Streams API and integration with Akka Streams.
  • Containerization and Orchestration: Understanding of containerization technologies like Docker and orchestration frameworks like Kubernetes.
  • Performance Tuning: Expertise in fine-tuning Akka applications for optimal performance and scalability.
  • Security: Understanding of security principles and experience with securing Akka applications.
  • Continuous Integration/Deployment: Knowledge of CI/CD pipelines and experience with tools like Jenkins or GitLab.
  • Team Leadership: Ability to lead and mentor a team of Akka developers and guide them in implementing best practices.

Expert/Team Lead

  • Advanced Akka APIs: Mastery of advanced Akka features like Akka Typed and Akka Persistence Query.
  • Performance Optimization at Scale: Extensive experience in optimizing the performance of Akka applications at scale.
  • Architectural Design: Ability to design and architect complex Akka-based systems.
  • Fault Tolerance and Resilience: Expertise in building fault-tolerant and resilient systems using Akka supervision strategies.
  • Cloud Technologies: Proficiency in leveraging cloud technologies like AWS or Azure for deploying Akka applications.
  • Microservices: Experience with building microservices architectures using Akka and related frameworks.
  • Big Data Integration: Knowledge of integrating Akka applications with big data frameworks like Apache Spark.
  • Performance Benchmarking: Ability to conduct performance benchmarking and analysis for Akka applications.
  • Code Review and Quality Assurance: Expertise in conducting code reviews and ensuring high-quality code standards.
  • Technical Documentation: Proficiency in writing technical documentation for Akka applications and APIs.
  • Agile Methodologies: Experience working in Agile development environments and familiarity with Scrum or Kanban.

TOP 14 Facts about Akka

  • Akka is an open-source toolkit and runtime for building highly concurrent, distributed, and fault-tolerant applications on the Java Virtual Machine (JVM).
  • It was first released in 2009 by Typesafe, which later became Lightbend.
  • Akka is written in Scala, a statically typed programming language that runs on the JVM, but it provides APIs for both Scala and Java.
  • One of the core concepts in Akka is the actor model, where actors are lightweight concurrent entities that communicate through asynchronous message passing.
  • Akka provides a high-level abstraction for building and managing actors, making it easier to create scalable and resilient applications.
  • It supports both local and remote actors, allowing for distributed computing and communication across multiple nodes or machines.
  • Akka uses an event-driven, non-blocking, and reactive programming model, which enables efficient utilization of system resources and better responsiveness.
  • It offers built-in mechanisms for handling failures and supervision of actors, ensuring fault tolerance and resilience in distributed systems.
  • Akka’s clustering module allows you to create clusters of actors that can span multiple nodes, providing fault-tolerant and elastic scaling capabilities.
  • It supports various message delivery semantics, such as at-most-once, at-least-once, and exactly-once, which can be useful in different scenarios.
  • Akka can be integrated with other technologies and frameworks, including Akka HTTP for building reactive web servers, Akka Streams for stream processing, and Akka Persistence for event sourcing and persistence.
  • It has a large and active community, with regular releases, extensive documentation, and a wide range of third-party libraries and plugins available.
  • Akka is widely used in industry for building high-performance and scalable applications, with notable adopters including companies like Intel, PayPal, and LinkedIn.
  • Performance benchmarks have shown that Akka can handle millions of messages per second with low latency, making it suitable for demanding workloads.

What are top Akka instruments and tools?

  • Akka Actors: Akka Actors is a powerful toolkit and runtime for building highly concurrent, distributed, and fault-tolerant applications in Java or Scala. It was first released in 2009 and has since become one of the most widely used tools in the Akka ecosystem. Akka Actors provide a simple yet powerful model for building scalable and resilient systems, allowing developers to easily create and manage lightweight, asynchronous, and message-driven actors.
  • Akka Streams: Akka Streams is a reactive streams library built on top of Akka Actors. It provides a high-level API for building scalable and efficient stream processing applications. With Akka Streams, developers can easily define complex stream processing pipelines using a declarative and composable API. It was first introduced in 2014 and has gained popularity for its simplicity and efficiency in handling large volumes of data in real-time.
  • Akka HTTP: Akka HTTP is a powerful and flexible toolkit for building HTTP-based applications and APIs in Scala or Java. It provides a high-performance server and client-side implementation of the HTTP protocol, allowing developers to easily build scalable and efficient web applications. Akka HTTP was first released in 2014 and has since become the de facto standard for building HTTP-based services in the Akka ecosystem.
  • Akka Cluster: Akka Cluster is a module in Akka that enables the building of distributed applications and services. It provides a fault-tolerant and scalable foundation for building clustered systems using the actor model. Akka Cluster was introduced in 2012 and has been widely adopted for building highly available and resilient distributed systems.
  • Akka Persistence: Akka Persistence is a tool that provides event sourcing capabilities for building persistent, stateful applications in Akka. It allows developers to easily store and recover the state of actors, making it ideal for building systems with strong consistency requirements. Akka Persistence was first released in 2013 and has been widely used in domains such as finance, gaming, and telecommunications.
  • Akka Monitoring: Akka Monitoring is a toolset for monitoring and managing Akka-based applications in production. It provides insights into the performance, health, and behavior of Akka actors and allows for real-time monitoring and troubleshooting. Akka Monitoring tools, such as Kamon and Lightbend Monitoring, help developers and operators gain visibility into their Akka applications and ensure optimal performance and reliability.
  • Akka Cluster Sharding: Akka Cluster Sharding is a module that allows for efficient distribution and management of stateful actors across a cluster of nodes. It simplifies the process of scaling and distributing stateful actors in a cluster, enabling developers to build highly scalable and fault-tolerant systems. Akka Cluster Sharding was introduced in 2013 and has been widely used in applications that require horizontal scalability and fault tolerance.
  • Akka Persistence Query: Akka Persistence Query is a tool that allows developers to query and analyze event-sourced data stored by Akka Persistence. It provides a high-level API for querying the event journal and offers a flexible and efficient way to extract insights from event-sourced systems. Akka Persistence Query was introduced in 2015 and has been used in a wide range of applications, including financial systems and IoT platforms.

Soft skills of a Akka Developer

Soft skills are essential for an Akka Developer to effectively collaborate with teams, communicate ideas, and adapt to changing requirements. Here are the soft skills required for Akka Developers at different levels:

Junior

  • Problem-solving: Ability to analyze and troubleshoot issues in Akka applications to ensure smooth functionality.
  • Teamwork: Collaborate effectively with colleagues, share knowledge, and contribute to the success of the team.
  • Communication: Clearly communicate ideas and updates to team members and stakeholders.
  • Time management: Prioritize tasks and deliver work within specified deadlines.
  • Adaptability: Quickly adapt to new technologies, frameworks, and project requirements.

Middle

  • Leadership: Take ownership of tasks, guide junior developers, and provide technical leadership to the team.
  • Problem-solving: Identify complex problems in Akka applications and propose efficient solutions.
  • Critical thinking: Evaluate different approaches and make informed decisions based on project requirements.
  • Collaboration: Foster effective collaboration among team members, stakeholders, and other teams.
  • Conflict resolution: Resolve conflicts and disagreements within the team in a diplomatic manner.
  • Time management: Manage multiple tasks and prioritize work to meet project deadlines.
  • Communication: Effectively communicate project updates and requirements to stakeholders.

Senior

  • Mentorship: Mentor and guide junior and middle developers to enhance their skills and knowledge in Akka.
  • Strategic thinking: Contribute to the long-term vision and strategy of the project and provide valuable insights.
  • Decision-making: Make informed decisions considering technical feasibility, business impact, and project goals.
  • Empathy: Understand and empathize with team members, stakeholders, and end-users to drive collaboration.
  • Negotiation: Negotiate with stakeholders to reach mutually beneficial agreements and resolve conflicts.
  • Presentation skills: Effectively present technical concepts and project updates to diverse audiences.
  • Time management: Efficiently manage time and resources to meet project milestones.
  • Communication: Communicate complex technical concepts in a clear and concise manner to stakeholders.

Expert/Team Lead

  • Strategic leadership: Provide overall technical guidance and leadership to the development team.
  • Project management: Plan, execute, and deliver projects on time and within budget.
  • Innovation: Drive innovation by exploring new technologies and proposing creative solutions.
  • Collaboration: Foster collaboration and synergy among team members and cross-functional teams.
  • Decision-making: Make critical decisions with a deep understanding of the business impact and technical feasibility.
  • Conflict resolution: Resolve conflicts and facilitate constructive discussions to ensure team harmony.
  • Adaptability: Adapt to changing project requirements, technologies, and market trends.
  • Presentation skills: Present project updates and technical concepts to both technical and non-technical stakeholders.
  • Strategic thinking: Develop and execute long-term strategies to achieve project and organizational goals.
  • Communication: Communicate effectively at all levels, from team members to executive stakeholders.
  • Empathy: Understand the needs and concerns of team members and stakeholders to build strong relationships.

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Manager
Maria Lapko
Global Partnership Manager