Senior Data Engineer (QA focus)

As a Senior Data Engineer you will be responsible for ensuring the accuracy, integrity and reliability of data across large-scale data platforms and pipelines. You will design and execute test strategies, test plans and test scripts to validate ETL/data flows — from source systems through transformations to target data stores — ensuring that data is correctly extracted, transformed, loaded and reconciled.

What You’ll Do – Key Responsibilities

• Design, write and execute comprehensive test plans, test cases and test scripts to validate ETL/data‑pipeline processes, data transformations, and data integrity (source‑to‑target, cross‑reference, reconciliation).

• Validate data extraction, transformation and loading processes for accuracy, completeness, consistency, schema integrity, referential integrity, deduplication, lineage and schema drift.

• Perform XREF (cross-reference) checks, source-to-target mapping validations, and data reconciliation between systems.

• Work with data lakes / data warehouse platforms — including environments using Databricks, Delta Lake tables, clusters, notebooks, SQL endpoints — to test data pipelines end-to-end.

• Develop and run automated data validation / regression testing scripts using Python or PySpark.

• Integrate testing into CI/CD pipelines and version-control practices using GitHub (branching, pull requests, test script management).

• Perform API testing (e.g. REST / JSON / XML) where data pipelines expose or consume APIs — validate request/response payloads, data integration correctness.

• Participate in System Integration Testing (SIT), support User Acceptance Testing (UAT) with business stakeholders, ensuring delivery meets acceptance criteria.

• Create and maintain test documentation: test plans, test cases, test data sets, traceability matrices, defect logs/reports.

• Collaborate with engineers, architects, data engineers and business users to ensure data quality throughout the delivery lifecycle.

• Report, track and support resolution of defects and data-quality issues.

Who You Are – Required Skills & Qualifications

• 4–7 years of hands-on experience in data testing / ETL testing / QA for data platforms or data warehouses.

• Strong proficiency in SQL for data validation, reconciliation, and complex query testing.

• Proven experience testing ETL pipelines built using Databricks, Azure Data Factory, SQL Server or comparable data‑integration tools/environments.

• Deep understanding of data validation concepts: deduplication, referential integrity, completeness, schema drift, data lineage.

• Hands‑on experience with Databricks notebooks, clusters, Delta Lake tables, SQL endpoints.

• Ability to write Python or PySpark scripts for automated data validation or regression testing.

• Familiarity with test automation frameworks or integrating testing into CI/CD pipelines.

• Comfortable using GitHub for version control, branching, pull requests, and test‑script management.

• Experience with API testing (REST/JSON/XML) — ability to validate API integration with data pipelines, request/response structures.

• Experience with System Integration Testing (SIT) and defect management workflows.

• Experience supporting UAT with business stakeholders — defining acceptance criteria, validating against business requirements.

• Skilled at creating test plans, test cases, test data, traceability matrices.

• Ideally: experience working in Financial Services or other regulated industry (compliance, data governance, audit-readiness).

• Strong attention to detail, structured and quality-first mindset.

• Excellent communication skills — able to work and collaborate with engineers, architects, business stakeholders.

Nice‑to‑Have / Bonus

• Familiarity with BI tools / reporting layers (e.g. dashboard testing, data visualization QA) or prior experience in validating BI/analytics output.

• Previous exposure to working in agile teams / SDLC environments.

• Experience with test‑management tools (e.g. JIRA, TestRail, X-Ray, or similar).

• Understanding of data‑warehouse concepts (star/snowflake schemas, fact & dimension tables).

What we offer for you

• Participation in full-cycle and diverse international projects

• Opportunity to work as a specialist or manager/team lead

• Constant career development with internal mentorship

• Access to a whole set of learning platforms, paid certifications

• Flexible working conditions, home working is allowed

• Attractive base salary & Wide range of benefits included cafeteria, bonuses, private health insurance package, life insurance, AYCM sport card, referral bonus, family-oriented benefits, company shares on a discount price