Introduction
At IBM, work is more than a job – it’s a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you’ve never thought possible. Are you ready to lead in this new era of technology and solve some of the world’s most challenging problems? If so, lets talk.

Your Role and Responsibilities
Asset Engineering is looking for a motivated and seasoned Data Engineer to join our global team to deliver outstanding results for both internal/external clients. You will be working in one of our top 10 most prized assets called Modern Data Accelerators. This product provides the foundation of data and analytics to harness the power of our clients’ data within their enterprises. MDA provides software tools for data, including curation, ingestion, operational controls, persist & publish, data product creation, governance, and data security. You will directly collaborate with the CTO of the asset and the technical team who architect, develop, enhance, and govern the asset.

Your Role and Responsibilities :

• Develop and maintain data pipelines for data ingestion, transformation, and loading.
• Optimize data pipelines for performance and scalability.
• Monitor data quality and troubleshoot issues.
• Collaborate with Data Architect and DevOps for infrastructure management.

Required Technical and Professional Expertise

• Strong programming skills in Python (or similar language).
• Experience building data pipelines and data transformation processes with DBT, DuckDB, Spark, and other ETL/ELT tools.
• Familiarity with data ingestion tools like Kafka (if applicable).
• Experience of cloud platforms for data storage and processing.
• Fluent in both English and Romanian

Preferred Technical and Professional Expertise

• Knowledge of Model Ops practices on cloud and containerization
• Familiarity with design lead development methodologies in complex data platforms and analytics
• Ability to work with data from the data platform and communicate insights effectively.