Data Engineering Technical Supervisor (Medior) – Databricks & Python

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

As part of the Thermo Fisher Scientific team, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the world’s toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer.

Thermo Fisher Scientific

Data Engineering Technical Supervisor (Medior) – Databricks & Python

Delivery & Stakeholder Collaboration

• Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Technology, or a related discipline, or equivalent professional experience.
• 4+ years of professional experience in data engineering, software engineering, or a related technical field.
• Strong hands-on experience with Python/PySpark, Databricks, Apache Spark, and SQL in production data engineering.
• Experience designing and operating production-grade ETL/ELT pipelines using Delta Lake and lakehouse architecture concepts.
• Solid understanding of data modeling, data quality, partitioning, performance optimization, and distributed data processing.
• Experience with Git-based development, automated testing, CI/CD, and code review.
• Demonstrated ability to troubleshoot complex technical issues and provide constructive engineering guidance.
• Experience mentoring engineers or providing technical leadership.
• Strong analytical, problem-solving, communication, and stakeholder-management skills.
• Experience with Databricks on AWS/GCP/Azure
• Experience with Unity Catalog and Databricks governance capabilities.
• Experience with data observability, monitoring, and pipeline automation.
• Experience optimizing Spark/Databricks workloads for performance and cost.

We are seeking a Data Engineering Technical Supervisor to provide hands-on technical leadership and day-to-day guidance to a team of data engineers building scalable, reliable, and high-quality data solutions. This role does not include people management responsibilities.

The role combines hands-on data engineering, technical supervision, mentoring, and project leadership, with a strong focus on Databricks, Python/PySpark, SQL, Delta Lake, and modern data engineering practices.

As part of the Data & Analytics team, the Technical Supervisor will collaborate with data engineers, BI developers, analysts, product owners, and business stakeholders while supporting the reliability, maintainability, and operational continuity of production ETL/ELT processes in Databricks.