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Henry A., Software Engineer with Python and Data Analytical Skills

Last Updated: 23 Apr 2024
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- 8+ years experience working with Python; - 5 years of experience as a BI and 4 years of experience with Tableau; - 8 years of experience with various data sets (ETL, Data Engineer, Data Quality Engineer); - 3 years of experience with Amazon Web Services (AWS), Google Cloud Platform (GCP); - Data Analytics/Engineering with Cloud Service Providers (AWS, GCP) - Experience working with MySQL, SQL, and PostgreSQL; - Deep abilities working with Kubernetes (K8s); - Hands-on scripting experience with Python; Microsoft Power BI, Tableau, Sisense, CI/CD principles, Data Validation, Data QA, SQL, Pipelines, ETL, and Automated web scraping. - Pet web3 projects (solidity, wallet integration) - Upper-intermediate English

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Python   8.5 yr.

Data Analysis

Data Analysis   6 yr.

Google Cloud Platform (GCP)

Google Cloud Platform (GCP)   4 yr.


Tableau   4 yr.

Microsoft Power BI

Microsoft Power BI   4 yr.

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Andrii Sh., DevOps Engineer

Cherkasy, Ukraine
Last Updated: 4 Jul 2023

- 24 years of professional expertise in the IT industry; - 2+ years of work experience with Kubernetes; - 6+ years of experience with Docker; - Solid skills in working with AWS Cloud Platform; - Experience with blockchain projects on Ethereum and Polkadot; - Deep knowledge of building and supporting monitoring and alerting systems using Grafana and Prometheus; - Good understanding of work with Terraform. - Skilled in designing, building, and improvement of the IT infrastructure; - Experienced in the implementation of solutions on Microsoft\ Apple \ and Unix platforms - Deep understanding of building virtual and cloud environments; - Experience in building corporate backup systems;

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Kubernetes (K8s)

Kubernetes (K8s)

Amazon Web Services (AWS)

Amazon Web Services (AWS)





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Alex K., Data Engineer

Oradea, Romania
Last Updated: 13 Nov 2023

- Senior Data Engineer with a strong technology core background in companies focused on data collection, management, and analysis. - Proficient in SQL, NoSQL, Python, Pyspark, Oracle PL/SQL, Microsoft T-SQL, and Perl/Bash. - Experienced in working with AWS stack (Redshift, Aurora, PostgreSQL, Lambda, S3, Glue, Terraform, CodePipeline) and GCP stack (BigQuery, Dataflow, Dataproc, Pub/Sub, Data Studio, Terraform, Cloud Build). - Skilled in working with RDBMS such as Oracle, MySQL, PostgreSQL, MsSQL, and DB2. - Familiar with Big Data technologies like AWS Redshift, GCP BigQuery, MongoDB, Apache Hadoop, AWS DynamoDB, and Neo4j. - Proficient in ETL tools such as Talend Data Integration, Informatica, Oracle Data Integrator (ODI), IBM Datastage, and Apache Airflow. - Experienced in using Git, Bitbucket, SVN, and Terraform for version control and infrastructure management. - Holds a Master's degree in Environmental Engineering and has several years of experience in the field. - Has worked on various projects as a data engineer, including operational data warehousing, data integration for crypto wallets/De-Fi, cloud data hub architecture, data lake migration, GDPR reporting, CRM migration, and legacy data warehouse migration. - Strong expertise in designing and developing ETL processes, performance tuning, troubleshooting, and providing technical consulting to business users. - Familiar with agile methodologies and has experience working in agile environments. - Has experience with Oracle, Microsoft SQL Server, and MongoDB databases. - Has worked in various industries including financial services, automotive, marketing, and gaming. - Advanced English - Available in 4 weeks after approval for the project

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Amazon Web Services (AWS)

Amazon Web Services (AWS)

Google Cloud Platform (GCP)

Google Cloud Platform (GCP)

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Konstantin, Senior Full-Stack Engineer

Last Updated: 4 Jul 2023

- I have experience cooperating with clients from all over the world and building products related to various spheres: e-commerce, real estate, custom CRM, trading, social media and many more. Product tech design and full cycle of development and support. - Key skills - Product tech design and full cycle of development and support - Technical analysis, time & budget management - knowledge of Go, Rust and JavaScript/TypeScript (node.js/react.js) - knowledge of Database systems: RDBMS, noSQL - knowledge of code quality tools and systems, continuous integration and delivery - knowledge of AWS services - knowledge of QA processes, integration and e2e testing. - Upper- Intermediate English

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Ihor M., Senior Software Engineer (React Native Engineer)

Last Updated: 10 Aug 2023

- Senior Software Engineer with 6 years of experience in the IT industry, 5+ of them at cross-platform mobile development. - Mostly works with React and React Native. - He does his best to keep up with modern practices and modern technologies, that way he can offer clients the most up to date solutions that give the users of their application the best experience. - Team player and flexible in the working environment. - Responsible Engineer willing to grow professionally and create new effective solutions for business. - Upper-Intermediate English.

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React Native

React Native

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FAQs about RDBMS Development

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If you urgently need a verified and qualified RDBMS developer, and resources for finding the right candidate are lacking, UPSTAFF is exactly the service you need. We approach the selection of RDBMS developers professionally, tailored precisely to your needs. From placing the call to the completion of your task by a qualified developer, only a few days will pass.

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Undoubtedly, there are dozens, if not hundreds, of specialized services and platforms on the network for finding the right RDBMS engineer. However, only UPSTAFF offers you the service of selecting real qualified professionals almost in real time. With Upstaff, software development is easier than calling a taxi.

How are Upstaff RDBMS developers different? Arrow

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 RDBMS 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 RDBMS 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 RDBMS developer on board with a trial period to confirm that you’ve hired the right one. There are no termination fees or hidden costs.

How does Upstaff vet remote RDBMS engineers? Arrow

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 RDBMS 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

TOP 10 RDBMS Related Technologies

  • SQL

    SQL (Structured Query Language) is a fundamental language used for managing relational databases. It allows developers to store, retrieve, and manipulate data efficiently. SQL is supported by most RDBMS software and provides a standardized way to interact with databases.

  • Java

    Java is a widely used programming language that offers excellent support for RDBMS software development. It provides various libraries and frameworks, such as JDBC (Java Database Connectivity), which enables seamless integration with databases. Java’s object-oriented nature makes it suitable for building robust and scalable applications.

  • Python

    Python is a versatile language that has gained popularity in the RDBMS software development community. It offers several libraries, including SQLAlchemy and Django ORM, which simplify database operations. Python’s simplicity and readability make it a preferred choice for data manipulation and analysis tasks.

  • .NET

    .NET is a framework developed by Microsoft that supports RDBMS software development. It provides ADO.NET, a data access technology that allows developers to interact with databases using various languages like C# and VB.NET. .NET offers a wide range of tools and libraries for building robust database-driven applications.

  • PHP

    PHP is a popular scripting language widely used in web development, including RDBMS software development. It offers MySQLi and PDO extensions, which provide seamless connectivity with MySQL and other databases. PHP’s simplicity and extensive community support make it a preferred choice for database-driven web applications.

  • JavaScript

    JavaScript is a versatile scripting language that can be used for client-side and server-side RDBMS software development. It offers frameworks like Node.js and libraries like Sequelize, which facilitate database operations. JavaScript’s widespread adoption and compatibility make it a valuable tool for building interactive web applications.

  • C#

    C# is a robust and modern programming language developed by Microsoft. It is widely used in RDBMS software development, especially for building applications using Microsoft SQL Server. C# offers powerful data access technologies like ADO.NET and Entity Framework, making it a suitable choice for database-driven applications.

Cases when RDBMS does not work

  1. When dealing with unstructured or semi-structured data:
  2. RDBMS is designed to handle structured data with well-defined schemas. However, when dealing with unstructured or semi-structured data like text documents, social media posts, or log files, it becomes challenging to fit such data into a rigid table structure. RDBMS lacks the flexibility to handle these types of data effectively.

  3. When scalability and high availability are crucial:
  4. RDBMS may face limitations in terms of scalability and high availability. As the amount of data and the number of users increases, the performance of an RDBMS can degrade. Scaling an RDBMS vertically, by adding more powerful hardware, can be costly and eventually reach its limits. Additionally, ensuring high availability in a distributed environment can be complex and may result in increased downtime.

  5. When the need for real-time data processing arises:
  6. RDBMS is primarily optimized for transactional processing, which involves reading and writing data in a structured manner. However, when it comes to real-time data processing, such as real-time analytics or streaming data, RDBMS might not be the most efficient choice. Processing large volumes of data in real-time requires specialized tools like stream processing frameworks or NoSQL databases designed for high-throughput ingestion and low-latency queries.

  7. When there is a requirement for flexible schema design:
  8. In an RDBMS, the schema is defined upfront, and any changes to the schema can be time-consuming and disruptive. This rigid schema design can be problematic when dealing with evolving or rapidly changing data structures. NoSQL databases offer flexible schema designs, allowing for easy adaptation to changing data requirements without requiring complex schema migrations.

  9. When the data model is hierarchical or graph-based:
  10. RDBMS works best with tabular data and relationships defined through foreign keys. However, when the data model is hierarchical (like XML or JSON) or graph-based (like social networks or recommendation systems), RDBMS might not be the most suitable choice. Specialized databases like XML databases or graph databases provide more efficient storage and querying mechanisms for such data models.

Soft skills of a RDBMS Developer

Soft skills are essential for RDBMS developers as they not only need technical expertise but also interpersonal skills to effectively communicate and collaborate with others. Here are the soft skills required at different levels of experience:


  • Attention to Detail: Ability to meticulously analyze and review database structures for accuracy and completeness.
  • Problem-Solving: Aptitude for identifying and resolving issues related to database performance and functionality.
  • Teamwork: Willingness to work collaboratively with peers and contribute to group projects.
  • Time Management: Ability to prioritize tasks and meet deadlines in a fast-paced development environment.
  • Communication: Strong verbal and written communication skills to effectively convey ideas and share information with team members.


  • Leadership: Capability to take ownership of projects and guide junior developers in executing tasks effectively.
  • Adaptability: Flexibility to adapt to changing project requirements and embrace new technologies and methodologies.
  • Critical Thinking: Proficiency in analyzing complex problems and proposing innovative solutions.
  • Mentoring: Willingness to mentor junior developers and assist them in enhancing their technical skills.
  • Collaboration: Ability to collaborate with stakeholders, such as business analysts and system architects, to understand requirements and design efficient database structures.
  • Conflict Resolution: Skill to handle conflicts and disagreements within the team in a constructive manner.
  • Time Management: Efficiently manage multiple projects and deadlines simultaneously.


  • Strategic Thinking: Capability to align database design and development with organizational goals and objectives.
  • Project Management: Proficiency in overseeing the entire database development lifecycle, including planning, execution, and monitoring.
  • Decision-Making: Ability to make informed decisions regarding database design, performance optimization, and scalability.
  • Communication: Excellent communication skills to effectively interact with stakeholders and present complex technical concepts in a clear and concise manner.
  • Collaboration: Collaborate with cross-functional teams to ensure seamless integration of database systems with other software components.
  • Innovation: Ability to identify opportunities for process improvement and implement innovative solutions.
  • Conflict Resolution: Skill to resolve conflicts and promote a harmonious work environment.
  • Knowledge Sharing: Willingness to share knowledge and mentor junior team members to enhance their skills and expertise.

Expert/Team Lead

  • Strategic Leadership: Ability to provide strategic direction to the team and drive the overall database architecture and design.
  • Team Management: Proficiency in managing a team of developers, assigning tasks, and ensuring their professional growth.
  • Technical Expertise: Extensive knowledge and expertise in RDBMS technologies, performance optimization, and database administration.
  • Problem-Solving: Ability to tackle complex database-related challenges and provide innovative solutions.
  • Decision-Making: Skill to make critical decisions regarding technology selection, project prioritization, and resource allocation.
  • Stakeholder Management: Ability to effectively manage relationships with stakeholders and ensure alignment between business requirements and technical solutions.
  • Strategic Planning: Capability to plan and execute long-term database strategies to support the organization’s growth and scalability.
  • Innovation: Promote a culture of innovation within the team and drive the adoption of new technologies and best practices.
  • Continuous Learning: Stay updated with the latest advancements in RDBMS technologies and industry trends.
  • Communication: Excellent communication skills to convey complex technical concepts to both technical and non-technical stakeholders.
  • Collaboration: Foster collaboration between development teams, system architects, and business analysts to ensure effective database design and implementation.

What are top RDBMS instruments and tools?

  • Oracle Database: Oracle Database is one of the most popular and widely used relational database management systems (RDBMS). It was first introduced in 1979 by Oracle Corporation. Oracle Database offers a wide range of features and capabilities, including high performance, scalability, and advanced security. It is known for its robustness and is commonly used in large enterprises and organizations.
  • Microsoft SQL Server: Microsoft SQL Server is another widely used RDBMS developed by Microsoft. It was first released in 1989 and has since become a popular choice for many businesses. SQL Server offers various editions tailored for different needs, ranging from small businesses to large enterprises. It provides a comprehensive set of tools and features for data management, business intelligence, and analytics.
  • MySQL: MySQL is an open-source RDBMS that was first released in 1995. It is known for its ease of use, performance, and scalability. MySQL is widely used in web applications and is a popular choice for small to medium-sized businesses. It is used by many popular websites and platforms, including Facebook, Twitter, and YouTube.
  • PostgreSQL: PostgreSQL is an open-source RDBMS known for its reliability and robustness. It was first released in 1996 and has a strong focus on standards compliance. PostgreSQL offers advanced features such as support for JSON, full-text search, and geospatial data. It is commonly used in both small and large-scale applications and is known for its ability to handle high volumes of data.
  • IBM Db2: IBM Db2 is a family of RDBMS products developed by IBM. It was first introduced in 1983 and has evolved over the years to cater to different platforms and use cases. Db2 offers features such as advanced analytics, in-memory computing, and integration with AI technologies. It is widely used in enterprise environments and is known for its scalability and reliability.
  • SQLite: SQLite is a lightweight, self-contained, and serverless RDBMS. It was first released in 2000 and is designed to be embedded into applications. SQLite is widely used in mobile applications, desktop software, and embedded systems. Despite its small size, it provides a full set of SQL features and is known for its simplicity and efficiency.
  • Amazon RDS: Amazon RDS (Relational Database Service) is a fully managed database service offered by Amazon Web Services (AWS). It supports multiple RDBMS engines such as MySQL, PostgreSQL, Oracle, and SQL Server. Amazon RDS simplifies the management and administration of databases by handling tasks such as backups, patching, and scaling. It is widely used by businesses to deploy and manage databases in the cloud.
  • Google Cloud Spanner: Google Cloud Spanner is a globally distributed and horizontally scalable RDBMS offered by Google Cloud Platform (GCP). It was introduced in 2017 and is designed for mission-critical applications that require high availability and strong consistency. Cloud Spanner combines the benefits of traditional RDBMS with the scalability and global reach of a NoSQL database.

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

Seniority NameYears of ExperienceResponsibilities and ActivitiesAverage Salary (USD/year)
Junior Developer0-2 yearsAssisting with basic coding tasks, bug fixing, and testing under close supervision. Learning and gaining experience in various programming languages and frameworks.$50,000 – $70,000
Middle Developer2-5 yearsDeveloping software features and components, participating in code reviews, and collaborating with a team to deliver high-quality code. Taking on more complex tasks and working more independently.$70,000 – $90,000
Senior Developer5-10 yearsLeading the development of complex software systems, designing architectural solutions, mentoring junior and middle developers, and actively contributing to the team’s technical strategy. Taking ownership of critical projects and driving them to success.$90,000 – $120,000
Expert/Team Lead Developer10+ yearsProviding technical leadership, managing a team of developers, collaborating with stakeholders to define project goals and requirements, and ensuring the delivery of high-quality software solutions. Responsible for the overall technical direction and success of the team.$120,000 – $150,000+

Pros & cons of RDBMS

8 Pros of RDBMS

  • RDBMS ensures data integrity by enforcing referential integrity constraints, entity integrity constraints, and domain constraints. This helps maintain the accuracy and consistency of the data.
  • RDBMS provides a structured and organized approach to data storage and retrieval. It uses tables, rows, and columns to store data, allowing for efficient data management.
  • RDBMS offers a high level of data security. It provides features like user authentication, access control, and encryption to protect sensitive data from unauthorized access.
  • RDBMS supports concurrent access to the data by multiple users. It employs locking mechanisms to ensure data consistency and prevent conflicts when multiple users try to access or modify the same data simultaneously.
  • RDBMS allows for easy scalability. With the ability to add or modify tables, columns, and relationships, RDBMS can accommodate changing business requirements and growing data volumes without significant disruptions.
  • RDBMS provides a standardized query language, such as SQL (Structured Query Language), which allows users to retrieve, manipulate, and analyze data efficiently.
  • RDBMS offers data independence. It separates the logical structure of the data from its physical storage, enabling developers to make changes to the database schema without affecting the applications or queries that use the data.
  • RDBMS provides built-in backup and recovery mechanisms. It allows for regular backups of the database, ensuring that data can be restored in case of hardware failures, software errors, or human mistakes.

8 Cons of RDBMS

  • RDBMS can be expensive to implement and maintain. Licensing costs, hardware requirements, and ongoing maintenance can add up, especially for large-scale deployments.
  • RDBMS may have limitations in handling certain types of data, such as unstructured or semi-structured data. While some RDBMS systems have introduced features to handle such data, they may not be as efficient as specialized solutions.
  • RDBMS can experience performance bottlenecks when dealing with complex queries or large datasets. Optimization techniques and proper indexing are required to ensure optimal performance.
  • RDBMS relies on a fixed schema, which can make it challenging to accommodate frequent changes in the data structure. Altering the schema may involve downtime or complex migration processes.
  • RDBMS may not be suitable for distributed computing environments where data needs to be stored and processed across multiple nodes or locations. The centralized nature of RDBMS can introduce latency and scalability challenges.
  • RDBMS may have a steep learning curve for developers who are new to the relational model and SQL. It requires understanding of relational theory and query optimization techniques to utilize the database effectively.
  • RDBMS may not be the best choice for real-time or high-speed data processing scenarios. The overhead of transaction management and durability guarantees can impact the performance in such cases.
  • RDBMS can be vulnerable to single points of failure. If the database server fails, it can lead to downtime and data unavailability unless proper redundancy and failover mechanisms are in place.

TOP 10 Facts about RDBMS

  • RDBMS stands for Relational Database Management System.
  • It is a type of database management system that is based on the relational model of data.
  • RDBMS organizes data into tables, which consist of rows and columns.
  • It uses a structured query language (SQL) for managing and manipulating data.
  • RDBMS provides data integrity by enforcing constraints such as primary keys, foreign keys, and data types.
  • It supports ACID (Atomicity, Consistency, Isolation, Durability) properties for transactions, ensuring reliability and consistency of data.
  • RDBMS allows for efficient data retrieval and manipulation through the use of indexes.
  • It enables data normalization, which reduces data redundancy and improves data integrity.
  • RDBMS provides a high level of scalability, allowing for the management of large amounts of data.
  • It is widely used in various industries and applications, including banking, e-commerce, healthcare, and more.

How and where is RDBMS used?

Case NameCase Description
Data WarehousingRDBMS development is widely used in data warehousing, where large volumes of structured data are stored and organized for analysis and reporting. The relational database model allows for efficient data storage, retrieval, and aggregation, making it an ideal solution for data warehousing. RDBMS development enables businesses to handle complex queries, perform multidimensional analysis, and generate meaningful insights from their data.
Online Transaction Processing (OLTP)RDBMS development is commonly employed in OLTP systems, where real-time transactional processing is crucial. RDBMS provides ACID (Atomicity, Consistency, Isolation, Durability) compliance, ensuring data integrity and reliability. It allows businesses to efficiently handle concurrent transactions, maintain consistency, and support high-volume transactional workloads. OLTP systems powered by RDBMS are widely used in sectors such as banking, e-commerce, and telecommunications.
Customer Relationship Management (CRM)RDBMS development plays a vital role in CRM applications, which are designed to manage and analyze customer data. RDBMS allows for the efficient storage and retrieval of customer information, such as contact details, purchase history, and interactions. This enables businesses to personalize customer experiences, track sales pipelines, and generate actionable insights for targeted marketing campaigns.
Inventory ManagementRDBMS development is instrumental in inventory management systems, where efficient tracking and control of stock levels are essential. RDBMS enables businesses to store and manage product information, inventory quantities, and movement. It facilitates real-time updates, accurate inventory tracking, and seamless integration with other business processes such as sales, purchasing, and logistics.
Human Resources ManagementRDBMS development is widely utilized in human resources management systems, which encompass various HR functions such as employee records, payroll, benefits administration, and performance management. RDBMS allows for efficient storage, retrieval, and analysis of HR data, enabling businesses to streamline HR processes, ensure data accuracy, and generate valuable insights for workforce planning and decision-making.
Content Management Systems (CMS)RDBMS development is a key component of content management systems, which are used to create, organize, and store digital content such as websites, blogs, and online publications. RDBMS enables efficient storage and retrieval of content, metadata, and user information. It supports features like version control, access control, and content indexing, allowing businesses to manage and deliver content seamlessly to users.
Financial SystemsRDBMS development is extensively utilized in financial systems for tasks such as accounting, budgeting, and financial reporting. RDBMS provides robust data management capabilities, ensuring accurate and secure financial data storage. It enables businesses to perform complex financial calculations, generate financial statements, and comply with regulatory requirements such as GAAP (Generally Accepted Accounting Principles) or IFRS (International Financial Reporting Standards).
Geographical Information Systems (GIS)RDBMS development is essential in GIS applications, which involve the storage, analysis, and visualization of spatial data. RDBMS allows for efficient storage and querying of geographic data, such as maps, coordinates, and attributes. It enables businesses to perform spatial analysis, generate maps, and support location-based decision-making in various domains, including urban planning, logistics, and environmental management.

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