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Artem, Scala Software Engineer with AWS Cloud

Ternopil, Ukraine
Last Updated: 4 Jul 2023
Scala

Scala

Java

Java

Amazon Web Services (AWS)

Amazon Web Services (AWS)

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Yurii P., Haskell and Scala Software Engineer

Ukraine
Last Updated: 4 Jul 2023

- Haskell, Cabal/Stack, GADTs/Type families, Generics, Servant, lenses, mtl, free monads - TDD, BDD, Unit, functional and integration testing - OOP, OOD (UML, Design patterns, SOLID, DI) - Functional programming approach, FRP, Redux, Event sourcing, base of Category theory - Upper-Intermediate English

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Haskell

Haskell   3 yr.

Scala

Scala   2 yr.

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Sciapan R, Scala and Java Software Engineer

Belarus
Last Updated: 4 Jul 2023

- 5+ years of experience in IT - Upper-intermediate English - Available ASAP

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Scala

Scala

Java

Java

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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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Scala

Scala

SQL

SQL

Amazon Web Services (AWS)

Amazon Web Services (AWS)

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Ihor K, Big Data & Data Science Engineer with BI & DevOps skills

Ukraine
Last Updated: 5 Mar 2024
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- Data Engineer with a Ph.D. degree in Measurement methods, Master of industrial automation - 16+ years experience with data-driven projects - Strong background in statistics, machine learning, AI, and predictive modeling of big data sets. - AWS Certified Data Analytics. AWS Certified Cloud Practitioner. - Experience in ETL operations and data curation - PostgreSQL, SQL, Microsoft SQL, MySQL, Snowflake - Big Data Fundamentals via PySpark, Google Cloud, AWS. - Python, Scala, C#, C++ - Skills and knowledge to design and build analytics reports, from data preparation to visualization in BI systems.

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AWS big data services

AWS big data services

AWS Quicksight

AWS Quicksight

Python

Python

Apache Kafka

Apache Kafka

Data Pipelines (ETL)

Data Pipelines (ETL)

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Наталья Кравцова
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FAQs about Scala Development

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AI tools and expert human reviewers in the vetting process are combined with a track record and historically collected feedback from clients and teammates. On average, we save over 50 hours for client teams in interviewing Scala candidates for each job position. We are fueled by a passion for technical expertise, drawn from our deep understanding of the industry.

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Our journey starts with a 30-minute discovery call to explore your project challenges, technical needs, and team diversity. Meet Carefully Matched Scala Talents. Within 1-3 days, we’ll share profiles and connect you with the right talents for your project. Schedule a call to meet engineers in person. Validate Your Choice. Bring a new Scala developer on board with a trial period to confirm that you’ve hired the right one. There are no termination fees or hidden costs.

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Upstaff Managers conduct an introductory round with potential candidates to assess their soft skills. Additionally, the talent’s hard skills are evaluated through testing or verification by a qualified developer during a technical interview. The Upstaff Staffing Platform stores data on past and present Scala candidates. Upstaff managers also assess talent and facilitate rapid work and scalability, offering clients valuable insights into their talent pipeline. Additionally, we have a matching system within the platform that operates in real-time, facilitating efficient pairing of candidates with suitable positions.

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Table of Contents

Soft skills of a Scala Developer

Soft skills are essential for a Scala Developer to thrive in their role, complementing their technical expertise with effective communication and collaboration abilities. Here are the soft skills required at different levels of experience:

Junior

  • Adaptability: Ability to quickly learn new concepts and technologies in a fast-paced environment.
  • Strong Problem-Solving: Aptitude to analyze and solve complex problems efficiently.
  • Attention to Detail: Thoroughness in writing clean and well-documented code.
  • Teamwork: Collaboration skills to work effectively with other team members.
  • Time Management: Capability to prioritize tasks and meet deadlines.

Middle

  • Communication: Excellent verbal and written communication skills to express ideas and technical concepts clearly.
  • Leadership: Capability to take charge of projects and guide junior team members.
  • Mentoring: Willingness to share knowledge and provide guidance to less experienced developers.
  • Conflict Resolution: Ability to handle conflicts and reach consensus within the team.
  • Initiative: Proactive approach to identify opportunities for improvement and take necessary actions.
  • Adaptability: Flexibility to adapt to changing project requirements and technologies.
  • Time Management: Efficiently manage time and resources to meet project goals.

Senior

  • Professionalism: Exhibit a high level of professionalism and integrity in all interactions.
  • Client Relations: Expertise in building and maintaining strong relationships with clients.
  • Strategic Thinking: Ability to think long-term and align technical solutions with business objectives.
  • Project Management: Proficiency in managing complex projects from planning to execution.
  • Decision-Making: Aptitude to make informed decisions and guide the team towards successful outcomes.
  • Innovation: Drive to explore new technologies and approaches to enhance development processes.
  • Empathy: Understanding and considering the perspectives and needs of stakeholders.
  • Team Building: Skill in building cohesive and high-performing teams.

Expert/Team Lead

  • Visionary Leadership: Ability to set a clear vision and inspire the team towards achieving it.
  • Strategic Planning: Proficiency in developing long-term strategies and roadmaps for projects.
  • Technical Expertise: Deep understanding and mastery of Scala programming language and related technologies.
  • Collaboration: Skill in fostering a collaborative and inclusive work environment.
  • Influence: Ability to influence and negotiate with stakeholders to drive project success.
  • Innovation: Track record of introducing innovative solutions and practices.
  • Knowledge Sharing: Actively share knowledge and expertise with the team and wider community.
  • Conflict Resolution: Expertise in resolving conflicts and promoting a harmonious work environment.
  • Decision-Making: Make informed decisions based on a comprehensive understanding of the project and business requirements.
  • Continuous Learning: Commitment to continuous learning and staying updated with industry trends.
  • Strategic Partnerships: Ability to build strategic partnerships and collaborations to enhance project outcomes.

Cases when Scala does not work

  1. Large-scale data processing: Scala is not the best choice for large-scale data processing tasks compared to languages like Python or Java. Scala’s performance may be hindered in scenarios where data processing requires extensive parallelism or distributed computing. Python’s libraries like Pandas and Apache Spark in Java provide better tools and frameworks for big data processing.
  2. Application startup time: Scala applications tend to have longer startup times compared to applications written in languages like Java or C++. This can be a problem in scenarios where fast application startup is crucial, such as serverless computing or microservices architecture.
  3. Memory usage: Scala applications can consume more memory compared to applications written in other languages. This can be a concern in resource-constrained environments or when aiming for optimal memory usage, such as mobile or embedded systems.
  4. Learning curve: Scala has a steeper learning curve compared to some other programming languages. The functional programming paradigm, as well as the complex syntax and features of Scala, can make it more challenging for beginners or developers coming from object-oriented programming backgrounds.
  5. Library support: While Scala has a rich ecosystem of libraries and frameworks, it may not have the same breadth and depth of libraries as more established languages like Python or Java. This can be a limitation when looking for specific functionality or when relying on community support.
  6. Tooling and IDE support: Although Scala has improved in terms of tooling and IDE support over the years, it still may not match the level of maturity and robustness found in other languages. IDEs like IntelliJ IDEA provide good Scala support, but there might be occasional issues or limitations compared to the seamless experience offered by IDEs for Java or Python.

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

  • Scala was created in 2003 by Martin Odersky, a professor at École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland.
  • Scala stands for “Scalable Language” and was designed to address the limitations of Java, combining object-oriented and functional programming concepts.
  • The language is statically typed, which means that type checking is done at compile-time, resulting in safer and more efficient code.
  • Scala runs on the Java Virtual Machine (JVM) and seamlessly interoperates with existing Java code, allowing developers to leverage their Java knowledge and libraries.
  • One of Scala’s key features is its support for functional programming, including higher-order functions, immutability, and pattern matching.
  • Scala introduced the concept of traits, which are similar to interfaces but can also contain concrete method implementations, promoting code reuse and modularity.
  • With the release of Scala 2.8 in 2010, the language introduced parallel collections, enabling developers to easily write parallel and concurrent code.
  • Scala has a powerful type inference system, which allows developers to write concise code without sacrificing type safety.
  • The Play Framework, a popular web application framework, is written in Scala and leverages its features to provide a highly productive and scalable development experience.
  • Scala has a vibrant and active community, with numerous open-source libraries and frameworks available for various domains, such as Akka for concurrent and distributed systems.
  • Spark, a widely used big data processing framework, was originally developed in Scala and still provides a Scala API, showcasing the language’s suitability for data-intensive applications.
  • The Scala ecosystem includes build tools like sbt and build automation tools like ScalaTest and ScalaCheck for testing and property-based testing.
  • Scala’s expressive syntax and concise code make it a favorite among developers, leading to increased productivity and reduced code verbosity.
  • Scala has a strong presence in the industry, with companies like Twitter, LinkedIn, and Airbnb using it for their backend systems.

What are top Scala instruments and tools?

  • Scala: Scala is a general-purpose programming language that combines object-oriented programming with functional programming. It was created by Martin Odersky and first released in 2003. Scala has gained popularity for its ability to seamlessly integrate with Java and its robust support for concurrency. It is widely used in industries like finance, technology, and data science.
  • Sbt: Sbt, short for “Scala Build Tool,” is the de-facto build tool for Scala projects. It provides a simple and intuitive way to manage project dependencies, compile code, run tests, and package applications. Sbt has a rich ecosystem of plugins and is known for its incremental compilation, which significantly speeds up development cycles.
  • ScalaTest: ScalaTest is a popular testing framework for Scala applications. It offers a comprehensive set of testing styles and assertions, allowing developers to write expressive and readable tests. ScalaTest also provides integrations with popular testing libraries like JUnit and TestNG.
  • Play Framework: Play Framework is a web application framework that is built using Scala. It follows the MVC (Model-View-Controller) architectural pattern and offers powerful features for building scalable and reactive web applications. Play Framework has gained traction for its developer-friendly APIs and built-in support for non-blocking I/O.
  • Akka: Akka is a toolkit and runtime for building highly concurrent, distributed, and fault-tolerant applications. It is based on the Actor model of computation and provides abstractions for managing concurrency, scalability, and resilience. Akka has been widely adopted in industries like finance, gaming, and telecommunications.
  • Spark: Apache Spark is a fast and distributed data processing engine that provides an interface for programming entire clusters with implicit data parallelism and fault tolerance. While Spark is not exclusive to Scala, it has native support for Scala and provides a Scala API that allows developers to leverage the full power of Spark’s capabilities.
  • Scalaz: Scalaz is a library that extends the functionality of Scala’s standard library with additional abstractions and utilities. It focuses on functional programming and provides features like immutable data structures, type classes, monads, and functional combinators. Scalaz is widely used in projects that embrace functional programming paradigms.
  • Slick: Slick is a modern database query and access library for Scala. It provides a type-safe API for interacting with relational databases, allowing developers to write database queries using Scala’s expressive and composable language features. Slick supports various database backends and offers features like asynchronous query execution and schema evolution.
  • Ammonite: Ammonite is an advanced Scala REPL (Read-Eval-Print Loop) that provides a more interactive and feature-rich experience compared to the standard Scala REPL. It offers features like syntax highlighting, tab completion, and built-in support for running scripts. Ammonite is often used for exploring and experimenting with Scala code.

Pros & cons of Scala

9 Pros of Scala

  • Scala is a statically typed language, which means that it catches errors at compile-time rather than at runtime. This helps in writing safer and more reliable code.
  • Scala is highly scalable and can handle large-scale applications. It can seamlessly integrate with existing Java code, making it an ideal choice for organizations that have a significant investment in Java.
  • Scala has a concise and expressive syntax that allows developers to write code that is more readable and maintainable. It supports functional programming paradigms, which can lead to more modular and reusable code.
  • Scala has a powerful type system that allows for advanced type inference and pattern matching. This makes it easier to write code that is both type-safe and flexible.
  • Scala has excellent support for concurrency and parallelism. It includes built-in support for actor-based concurrency model, which makes it easier to write concurrent and distributed applications.
  • Scala has a rich ecosystem of libraries and frameworks, such as Akka, Spark, and Play, that make it easy to build a wide range of applications.
  • Scala has a strong community and active development, which means that there are plenty of resources and support available for developers.
  • Scala is compatible with existing Java libraries and frameworks, which allows developers to leverage the vast Java ecosystem.
  • Scala is a versatile language that can be used for a variety of purposes, including web development, data analysis, and machine learning.

9 Cons of Scala

  • Scala has a steep learning curve, especially for developers who are not familiar with functional programming concepts.
  • Scala’s advanced features and powerful type system can sometimes make the code more complex and harder to understand.
  • Scala code can be slower to compile compared to other languages, especially when dealing with large codebases.
  • Scala’s interoperation with Java can sometimes be challenging, especially when dealing with complex Java libraries or frameworks.
  • Scala has a smaller user base compared to more mainstream languages like Java or Python, which means that finding experienced Scala developers can be more difficult.
  • Scala’s syntax can be overwhelming for beginners, especially if they are not familiar with functional programming concepts.
  • Scala’s ecosystem, while growing, is not as mature as some other languages, which means that there may be fewer libraries and frameworks available for specific use cases.
  • Scala’s documentation can sometimes be lacking in depth and examples, which can make it harder for developers to learn and use the language effectively.
  • Scala’s tooling, while improving, is still not as robust as some other languages, which can make the development experience less smooth.

TOP 10 Scala Related Technologies

  • Scala

    Scala is a general-purpose programming language that combines object-oriented and functional programming features. It is designed to be concise, expressive, and scalable, making it an ideal choice for building robust and scalable software applications.

  • Akka

    Akka is a toolkit and runtime for building highly concurrent, distributed, and fault-tolerant applications on the JVM. It provides actors as a high-level abstraction for building concurrent and scalable applications, making it a popular choice for Scala software development.

  • Play Framework

    Play Framework is a web application framework built on top of Scala, providing a lightweight and reactive programming model. It offers a powerful set of features for building web applications, including built-in support for asynchronous programming, REST APIs, and real-time communication.

  • Slick

    Slick is a modern database query and access library for Scala. It provides a type-safe and reactive way to interact with databases, allowing developers to write concise and composable database queries. Slick integrates seamlessly with various database backends, making it a popular choice for Scala software development.

  • Spark

    Apache Spark is a fast and distributed computing system that provides in-memory data processing capabilities. It offers a high-level API in Scala for building big data processing applications, making it a popular choice for data-intensive Scala software development.

  • Cats

    Cats is a lightweight and modular functional programming library for Scala. It provides abstractions for working with functional programming concepts such as functors, monads, and applicative functors. Cats is widely used in Scala software development to write expressive and composable code.

  • Scalaz

    Scalaz is another popular functional programming library for Scala. It offers a rich set of abstractions and type classes for functional programming, allowing developers to write concise and expressive code. Scalaz is often used in Scala software development for its powerful functional programming features.

How and where is Scala used?

Case NameCase Description
Big Data ProcessingScala is widely used in big data processing frameworks such as Apache Spark. Its functional programming capabilities and ability to handle large-scale data sets make it a popular choice for processing and analyzing vast amounts of data efficiently. Scala’s ability to seamlessly integrate with Java libraries further enhances its usefulness in big data applications.
Web DevelopmentScala’s versatility and scalability make it well-suited for web development. Its functional programming features and expressive syntax allow developers to write concise and maintainable code. Scala frameworks like Play and Lift provide robust tools for building high-performance web applications. Scala’s compatibility with Java also enables easy integration with existing Java-based web systems.
Machine LearningScala is increasingly being used in machine learning applications. Its functional programming paradigm and support for distributed computing make it a natural fit for machine learning algorithms that require parallel processing. Popular machine learning libraries such as Apache Mahout and Deeplearning4j have Scala APIs, enabling developers to leverage Scala’s capabilities in this field.
Concurrency and ParallelismScala’s actor model, inspired by Erlang, provides a powerful concurrency model that simplifies the development of concurrent and parallel applications. Actors in Scala allow for lightweight, thread-like entities that communicate through message passing, making it easier to reason about and manage concurrent code. This feature makes Scala a compelling choice for building highly concurrent systems.
Data Analysis and VisualizationScala’s integration with popular data processing and visualization libraries, such as Apache Spark and Apache Zeppelin, makes it a valuable tool for data analysis and visualization tasks. Scala’s functional programming capabilities and support for distributed computing allow developers to efficiently process and analyze large datasets and generate meaningful visualizations.
Financial SystemsScala’s strong type system, functional programming features, and compatibility with Java make it well-suited for developing financial systems. The ability to express complex business logic in a concise and type-safe manner reduces the likelihood of errors and enhances code maintainability. Scala frameworks like Akka provide additional support for building highly scalable and fault-tolerant financial applications.
Real-time StreamingScala, along with frameworks like Apache Kafka and Apache Flink, is commonly used for real-time streaming applications. Scala’s functional programming paradigm and support for distributed computing enable developers to process and analyze streaming data in real-time with ease. Its compatibility with Java libraries and seamless integration with existing systems make it an ideal choice for building robust and scalable streaming applications.

Hard skills of a Scala Developer

Hard skills of a Scala Developer:

Junior

  • Scala Basics: Understanding of the fundamental concepts and syntax of the Scala programming language.
  • Functional Programming: Knowledge of functional programming principles and the ability to write functional code using Scala.
  • Object-Oriented Programming: Familiarity with object-oriented programming concepts and the ability to apply them in Scala.
  • Scala Collections: Proficiency in using and manipulating Scala collections such as lists, maps, and sets.
  • Concurrency: Understanding of basic concurrency concepts and the ability to write concurrent code using Scala’s Futures and Promises.

Middle

  • Advanced Scala Concepts: Deep understanding of advanced Scala features like higher-order functions, pattern matching, and type classes.
  • Scala Frameworks: Experience with popular Scala frameworks like Akka, Play, and Spark.
  • Database Integration: Knowledge of integrating Scala applications with databases using frameworks like Slick or ScalaQuery.
  • Testing: Proficiency in writing unit tests and integration tests using Scala testing frameworks like ScalaTest or Specs2.
  • Build Tools: Experience with build tools like sbt and familiarity with the build process for Scala projects.
  • Web Development: Ability to develop web applications using Scala and frameworks like Play or Akka HTTP.
  • Performance Optimization: Understanding of performance optimization techniques and the ability to optimize Scala code for better performance.

Senior

  • Scalability and Distributed Systems: Expertise in building scalable and distributed systems using Scala and frameworks like Akka.
  • Functional Libraries: Experience with popular functional libraries in the Scala ecosystem like Cats, Scalaz, or ZIO.
  • Streaming and Big Data: Knowledge of streaming and big data processing frameworks like Apache Kafka, Apache Flink, or Apache Spark.
  • Microservices Architecture: Proficiency in designing and implementing microservices architecture using Scala and frameworks like Lagom or Finch.
  • Performance Tuning: Ability to identify and resolve performance bottlenecks in Scala applications through profiling and optimization techniques.
  • DevOps and Deployment: Experience with deploying and managing Scala applications in production environments using tools like Docker and Kubernetes.
  • Code Review and Mentoring: Ability to review code, provide constructive feedback, and mentor junior developers in Scala best practices.
  • System Design: Expertise in designing complex systems and architectures using Scala and related technologies.

Expert/Team Lead

  • Leadership Skills: Strong leadership skills to guide and mentor a team of Scala developers and drive successful project delivery.
  • Architectural Design: Ability to design scalable, maintainable, and resilient architectures for large-scale Scala applications.
  • Performance Engineering: Deep understanding of performance engineering principles and the ability to optimize the performance of complex Scala systems.
  • Domain-Driven Design: Proficiency in applying domain-driven design principles to design and implement scalable and modular Scala applications.
  • Functional Reactive Programming: Expertise in building reactive systems using functional reactive programming techniques and libraries like Akka Streams or Monix.
  • Code Quality and Best Practices: Ensuring adherence to coding standards, best practices, and code quality metrics in Scala codebases.
  • Technical Documentation: Ability to create comprehensive technical documentation, including architecture diagrams, design documents, and API specifications.
  • Continuous Integration and Delivery: Experience with setting up and configuring CI/CD pipelines for Scala projects using tools like Jenkins or GitLab CI/CD.
  • Performance Monitoring and Optimization: Proficiency in monitoring and optimizing the performance of Scala applications in production environments using tools like Grafana and Prometheus.
  • Team Collaboration: Excellent communication and collaboration skills to work effectively with cross-functional teams and stakeholders.
  • Project Management: Experience in managing and delivering complex Scala projects, including resource allocation, timeline management, and risk assessment.

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