We are seeking an experienced Senior Data Engineer to join our expanding team in Sofia. This is a full-time, hybrid position. The ideal candidate has 7+ years of professional experience in data engineering, database development, ETL processes, and software development, with a proven track record of building database-driven solutions that are scalable, performant, and maintainable.
This is a hands-on role. You will owe the design and delivery of significant parts of our data platform, contribute to architectural decisions, and help raise the technical bar across the team. Strong skills with Microsoft SQL Server, .NET C#, and cloud platforms such as Azure or AWS are essential.
Requirements
- Bachelor’s degree in Computer Science, Information Technology, or a related field, or equivalent practical experience.
- 7+ years of professional experience in data engineering, database development, and software development.
- Excellent proficiency with Microsoft SQL Server, including writing and optimizing complex queries, stored procedures, and indexes, as well as database management tasks such as query plan analysis, performance monitoring, backup and recovery, security, and high-availability configuration.
- Proven experience designing relational data models and strategies for storing and querying high-volume data in SQL Server, including partitioning, indexing strategies, and archiving.
- Solid experience in designing, building, and maintaining ETL processes and data pipelines in production environments.
- Strong hands-on experience building production applications in C# and the .NET ecosystem, including services, data access layers, and ETL components.
- Experience building and deploying solutions on cloud platforms such as Azure or AWS.
- Strong understanding of database design principles, scalability, performance tuning, and ensuring high availability.
- Experience with source control (Git) and CI/CD pipelines.
- Experience working in Agile/Scrum teams and with tools such as Jira and Confluence.
- Excellent communication skills—fluency in English is required.
- Exceptional problem-solving, creative thinking, and a willingness to seek, prove and employ bold and innovative solutions.
- Ability to work effectively in a hybrid work environment.
Nice to Have
- A strong plus is experience with NoSQL and analytics data stores such as Azure Data Explorer or OpenSearch, and with strategies for storing and querying high-volume data.
- A creative approach to data solutions, with experience working across mixed database environments (e.g., relational, NoSQL, and analytics stores).
- Exposure to infrastructure as code (e.g., Terraform, Bicep, or ARM templates).
- Familiarity with cloud data and integration services such as Azure Data Factory, Azure Functions, or their AWS equivalents.
- Ability to expose data solutions through well-designed libraries, APIs, or interfaces that make them easy to use and test.
Responsibilities
Solution Design and Architecture
- Contribute to the design and implementation of data engineering, database, and ETL solutions for key components of the platform.
- Participate in architectural discussions and decisions, ensuring solutions align with business and technical goals.
- Break down complex technical problems, propose practical options, and see them through delivery.
Data Pipeline and Database Development
- Build and maintain scalable, efficient data pipelines using C#/.NET and cloud services.
- Implement data transformation processes that preserve data integrity and quality.
- Develop and optimize database objects such as schemas, stored procedures, and indexes, with a focus on performance, scalability, and availability.
Cloud Infrastructure and Integration
- Develop, deploy, and optimize cloud-based data solutions on Azure or AWS.
- Contribute to infrastructure-as-code practices and help maintain reliable CI/CD pipelines.
Collaboration and Requirements
- Collaborate with Support, Operations, Product, and Engineering teams to deliver and support solutions.
- Share knowledge through code reviews, pairing, and mentoring less experienced engineers.
Quality Assurance
- Write testable, maintainable code and contribute to testing and automation frameworks.
- Investigate and resolve data issues, performing root cause analysis and putting preventive measures in place.
Continuous Improvement
- Evaluate new tools and technologies through research and proofs-of-concept.
- Keep up to date with industry’s best practices and bring relevant improvements to the team.
Documentation and Communication
- Produce clear, accurate documentation of data processes and systems.
- Follow company standards, policies, and regulatory requirements.
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