Data Engineer

Job Title: Data Engineer
Location: Cambridge, MA 02141
Work Arrangement: 100% Onsite
Position Summary

We are seeking a Contract Data Engineer to join the Data Architecture and Engineering team, where you will help build, monitor, and maintain complex data pipelines and integrations.

You will assist with all aspects of the data lifecycle, including ingestion, transformation, and data quality monitoring, while ensuring strong engineering practices.

You will work closely with engineers and stakeholders across Infrastructure & Operations (I&O), Lab IT, PI Tech, and the scientific community to translate 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 collaborate with technical teams and scientific stakeholders to deliver high-impact solutions that accelerate scientific discovery.
Key Responsibilities

• Build, monitor, and maintain complex data pipelines, integrations, and tools.
• Develop and maintain appropriate data models across various data systems and tools.
• Support the monitoring and development of data quality standards and processes.
• Gather requirements from scientific end users to ensure engineering solutions address their needs.
• Promote engineering best practices and contribute to the development of robust engineering standards.
• Establish processes and practices for metadata acquisition, management, and data lineage.
• Leverage generative AI tools and frameworks to accelerate pipeline development, data transformation, and metadata enrichment at scale.
• Collaborate with cross-functional teams to deliver secure, scalable, and reliable data engineering solutions.

Required Qualifications

• 2+ years of hands-on data engineering experience, preferably in life sciences, biotechnology, or healthcare environments.
• Experience building, monitoring, and maintaining production data pipelines.
• Strong proficiency in Python and SQL for data manipulation, pipeline development, and automation.
• Experience working with row-oriented and column-oriented databases, including relational and dimensional data modeling.
• Familiarity with cloud platforms and services, particularly AWS.
• Experience with modern data engineering tools and frameworks such as Dagster, Apache Spark, dbt, Apache Iceberg, Amazon Athena, Polars, and Git.
• Practical experience using generative AI tools, such as Claude Code, GPT-based tools, or similar technologies, to improve engineering efficiency and reduce repetitive development work.

Preferred Qualifications

• Experience supporting bioinformatics, cheminformatics, clinical data workflows, or other high-volume scientific data formats and modalities.
• Experience with semantic modeling and related technologies such as dbt Semantic Layer, Cube, or DAX.
• Familiarity with data quality tools such as Soda, Great Expectations, or similar solutions.
• Experience working with scientific software and Electronic Laboratory Notebooks (ELNs), particularly Benchling and CDD.
• Relevant certifications, such as AWS Solutions Architect Associate, AWS Data Analytics Specialty, or equivalent credentials.