Data Engineer Bucuresti - Ilfov, Romania Posted on 07​/24​/2026 Trending

We are seeking an experienced and highly motivated Data Engineer to design, build, and operate reliable data pipelines and analytics-ready datasets that power reporting and business decision-making. In this role, you will develop and optimize ETL/ELT processes using Python
, Azure Databricks
, and SQL
, integrating data across platforms including Microsoft SQL Server and PostgreSQL
. You will partner with analysts, data consumers, and engineering teams to translate business requirements into scalable, well-governed data products, applying strong engineering practices around testing, monitoring, performance, and data quality, while using AI-assisted development tools and generative AI to enhance productivity and solution quality. We are looking for someone with hands-on experience integrating AI capabilities into enterprise data workflows and a strong understanding of responsible AI principles, including data privacy, fairness, and explainability.

Key duties and responsibilities:

Data Pipeline Development (ETL/ELT):
Design, build, and maintain batch and/or incremental pipelines using Python, Azure Databricks, and SQL to ingest, transform, and curate data for analytics and downstream applications.

Orchestration, Scheduling & Reliability:
Automate and schedule pipeline execution, implement idempotent processing, and build monitoring/alerting and operational runbooks to ensure reliable, observable data products.

Production Operations Support:

Own day-to-day production support for data pipelines and reporting workflows, including incident triage and resolution, root-cause analysis, and proactive monitoring to meet SLAs and ensure data reliability.

Databricks Engineering:
Develop and optimize notebooks and jobs; implement reusable libraries, parameterized workflows, and cluster/job configurations; apply performance tuning techniques (partitioning, caching, query optimization) as appropriate.

SQL performance optimization:

Optimize schemas, tables, views, and SQL logic across Microsoft SQL Server and PostgreSQL. Troubleshoot performance issues and ensure data integrity through constraints, indexing, and query tuning.

Data Quality & Controls:

Define and implement validation rules, reconciliation checks, and automated tests to detect anomalies, enforce SLAs, and improve trust in reporting and analytics outputs.

AI Enablement & Productivity:

Use AI-assisted development tools and generative AI to improve engineering productivity, data pipeline quality, and documentation while maintaining strong validation and governance practices.

Required experience & competencies

• 5+ years in Data engineering roles.
• Strong Python for ETL, automation, and data transformations.
• Experience with Azure data services and Databricks operations.
• Proven experience with AI-assisted software development tools and workflows.
• Demonstrated ability to use generative AI to improve developer productivity and solution quality.
• Solid understanding of responsible AI principles, including data privacy, fairness, and explainability.
• Hands-on experience integrating AI capabilities into enterprise data or analytics applications.
• Degree in Computer Science, Management of Information Systems, or a related analytical field or equivalent experience.

Nice-to-haves:

• Experience with data quality testing and validation frameworks.
• Familiarity with Lakehouse concepts and Delta tables.
• Experience with PostgreSQL, including query and schema optimization.
• CI/CD for data pipelines using Azure Dev Ops or Gitlab or similar.
• Ability to integrate AI/ML model endpoints into data platforms and pipelines using Azure ML or similar.
• Advanced SQL for analytics, modeling, and performance tuning.
• Locations 11625 Rosewood Street, Leawood, KS, 66211, US

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