Work Schedule
- Standard Office Hours (40/wk)
Environmental Conditions
- Office
Job Description
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.
The Data Engineer will support the development, maintenance, and optimization of data solutions using the Databricks platform. This is an entry-level data engineering role designed for candidates with foundational experience in SQL, Python, cloud technologies, and modern data engineering concepts. The engineer will work as part of an Agile development team and collaborate with experienced data engineers, analysts, and business partners to build reliable data pipelines, data models, and analytics-ready datasets.
Responsibilities
- Develop and maintain data pipelines and data transformations using Databricks, SQL, Python, and PySpark.
- Assist with the ingestion, transformation, and processing of structured and semi-structured data from multiple source systems.
- Develop and maintain Databricks notebooks, pipelines, workflows, and jobs supporting data engineering and analytics use cases.
- Build and maintain data tables and datasets using Delta Lake and lakehouse architecture principles.
- Write, test, troubleshoot, and optimize SQL queries used for data processing, analysis, and reporting.
- Support the development of ETL/ELT pipelines that move and transform data across source systems, cloud storage, Databricks, and downstream applications.
- Work within an Agile Scrum team to design, develop, unit test, debug, document, and maintain data solutions based on defined functional and technical requirements.
- Collaborate with senior engineers and architects to ensure solutions follow established architecture, development standards, security requirements, and engineering best practices.
- Assist with defining data models, data structures, transformation logic, and information flows.
- Perform data validation and troubleshooting to help ensure the quality, consistency,