Data Engineer

LOCAL ONLY !


5 days onsite


2+ years of hands-on experience in data engineering - must have life sciences, biotech, or healthcare environments .


Title: Data Engineer


Location: Cambridge, MA 02141


Remote / Hybrid Schedule: 100% onsite


Duration: 4-6 months+

Position Summary: Data Engineer - Contractor Position Summary: We are seeking a Contract Data Engineer to join our Data Architecture and Engineering team where you will help build, monitor, and maintain complex data pipelines and integrations. Your will assist with all aspects of the data lifecycle including; ingestion, transformation, and data quality monitoring as well as helping to ensure good engineering practices. You will work closely with other engineers and stakeholders across Infrastructure & Operations I&O, Lab IT, PI Tech, and the scientific community to turn evolving scientific needs into secure, reliable and scalable data engineering solutions. This role goes beyond simply building pipelines: it requires strong cross-functional communication and the ability to work with stakeholders across Infrastructure & Operations I&O, Lab IT, PI Tech, and the scientific community to deliver high impact solutions that accelerate scientific discovery.


Responsibilities:


Build, monitor, and maintain complex data pipelines, integrations, and tools.


Build and maintain proper data models across various data systems and tools.


Assist in the monitoring and development of data quality and data quality standards.


Assist in requirements gathering with scientific end users to ensure engineering solutions address their needs.


Help ensure engineering best practices and assist in the development of robust engineering standards.


Help establish processes and practices for the acquisition and usage of metadata and data lineage.


Leverage generative AI tools and frameworks to accelerate pipeline development, data transformation, and metadata enrichment at scale.

Qualifications: Essential


2+ years of hands-on experience in data engineering, preferably in life sciences, biotech, or healthcare environments.


Experience building, monitoring, and maintaining data pipelines in a production environment.


Proficiency in Python and SQL for data manipulation, pipeline development, and system automation.

Experience with both row and column databases / relational and dimensional data modeling.

Familiarity with cloud platforms and services, particularly AWS. Experience with modern frameworks, and tools such as Dagster, Spark, dbt, Iceberg, Athena, Polars, Git, etc.


Practical experience using generative AI tools (e.g. Claude Code, GPT-based tools, etc.) to boost engineering velocity and reduce boilerplate.


Desired Experience


supporting bioinformatics, cheminformatics, clinical data workflows, or other high-volume scientific data modalities and formats.


Experience with semantic modeling and tools (e.g. dbt Semantic Layer, Cube, DAX. Familiarity with data quality tools such as Soda, Great Expectations, or similar.


Familiarity with scientific software and ELN's, particularly Benchling and CDD. Relevant certifications (e.g., AWS Solutions Architect Associate, Data Analytics Specialty, etc.).