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Aida Projektai Mb logo

Data Quality Engineer (Python & Databricks)

Aida Projektai Mb
Posted Jul 2, 2026, 7:15 PM UTC
🇷🇴Romania🏠Remote📁Data & Analytics
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For our customer , we are looking for a Data Quality Engineer (Python & Databricks) . Location: Romania (Remote) Contract Type: B2B In this role, you will be responsible for designing and maintaining automated data validation frameworks that ensure data consistency, accuracy, and integrity across cloud migration initiatives. Working closely with data engineers and platform teams, you will validate data pipelines, processing workflows, and cloud infrastructure while supporting large-scale migrations between AWS and GCP. You will develop automated quality gates, verify data parity across distributed systems, and integrate validation processes into CI/CD pipelines. This role combines strong Python development, data engineering, and cloud platform expertise to ensure production-ready, high-quality data solutions. The Ideal Candidate 4+ years of experience in Data Quality Engineering, Data Validation, or Data Engineering Strong Python programming skills for building automated validation frameworks Hands-on experience with Databricks and advanced SQL Experience validating data across distributed systems and cloud platforms Strong knowledge of Kafka, Redis, S3, GCS, and modern data processing architectures Experience with CI/CD pipelines and Jenkins or similar orchestration tools Understanding of cloud migration projects and data reconciliation techniques Excellent analytical, troubleshooting, and communication skills Experience working in Agile environments with English-speaking engineering teams What You Will Do Design and implement automated data validation pipelines using Python and Databricks Develop and maintain data parity checks across ETL and processing layers Validate data integrity across Kafka clusters and downstream systems Verify replication accuracy, object parity, and stored procedure consistency during cloud migrations Validate Airflow and Cloud Composer DAG execution, scheduling, retry logic, and alerting Build automated data quality gates integrated into CI/CD pipelines Monitor pipeline telemetry and provide validation evidence to support migration readiness Collaborate with engineering teams to identify, troubleshoot, and resolve data quality issues Leverage AI-assisted development tools to improve validation, test automation, and defect analysis What the Company Offers 100% remote work from Romania B2B contract Opportunity to work on enterprise-scale cloud migration and data platform initiatives Modern technology stack including Python, Databricks, AWS, GCP, Kafka, and Jenkins International engineering environment with English-speaking teams Exposure to large-scale distributed systems and cloud-native architectures Long-term project utilizing modern AI-assisted engineering practices Competitive compensation and opportunities for professional growth

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