Senior Data Engineer (Databricks)

Quick Facts

Senior Data Engineer role focused on building and improving production-grade data pipelines on Databricks.

Description

You will design scalable data pipelines on Databricks, standardize existing pipelines using a “gold standard” approach, and migrate/refactor legacy pipelines. You will develop data transformations with dbt and Python, support onboarding of new datasets across US and APAC regions, and optimize performance and resource usage under capacity constraints. You will collaborate with data architects and analytics teams and contribute to future Data Science and MLOps foundations.

Responsibilities

• Design and implement scalable data pipelines on Databricks
• Standardize existing pipelines (gold standard approach)
• Migrate and refactor legacy data pipelines
• Develop data transformations using dbt and Python
• Support onboarding of new datasets (US, APAC regions)
• Collaborate with data architects and analytics teams
• Contribute to Data Science and MLOps foundations
• Optimize performance and resource usage under capacity constraints

Requirements

• Strong experience as a Data Engineer
• Hands-on production-grade experience with Databricks
• Very good knowledge of Python for data processing
• Experience with dbt and data transformation layers
• Solid understanding of data pipeline design, orchestration, and scalability
• Experience migrating and refactoring legacy systems
• Experience with cloud-based data platforms (Azure/AWS/GCP)
• Knowledge of data modeling (medallion architecture, dimensional models)
• Experience working with financial or market data
• Familiarity with CI/CD practices for data pipelines
• Ability to work independently and take ownership of data solutions
• Strong communication skills and team collaboration mindset
• Work from the European Union region and hold a valid work permit

Benefits

• Opportunity to build and optimize modern data platforms on Databricks, supporting global dataset onboarding
• Contribute to future Data Science and MLOps foundations
• Work with data architects and analytics teams in a collaborative environment