Co-op, Data Engineering (open to Northeastern students only)

Ampersand Biomedicines•Boston, MA

1h•$25 - $40

About The Position

Ampersand Biomedicines is seeking a talented and proactive Data Engineering Co-op to join our growing Computational Biology team. This individual will play a hands-on role in designing, building, and maintaining the data pipelines that support our research and analytics teams, ensuring the seamless integration and availability of scientific data with the opportunity to contribute across data integration, visualization, and image analysis. The ideal candidate is a motivated student or early-career engineer with strong technical fundamentals, a keen eye for detail, and a passion for leveraging data to innovate in the biomedicine space.

Requirements

Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science, or a related field at Northeastern University.
Foundational experience through coursework, personal projects, or a prior internship - with data pipeline development, ETL concepts, or data integration.
Proficiency in SQL and familiarity with database technologies (e.g., PostgreSQL, MySQL, Redshift).
Strong programming skills in Python.
Exposure to cloud platforms (e.g., AWS, Azure, GCP) and their respective data services.
Familiarity with version control (git) and comfort working from the command line.
Excellent problem-solving skills and the ability to work independently as well as part of a collaborative team.
Strong communication skills, both written and verbal, with the ability to convey technical concepts to non-technical stakeholders.

Nice To Haves

Experience with data pipeline / orchestration or big data tools (e.g., Apache Airflow, AWS Glue, Spark).
Familiarity with data warehousing or lakehouse formats (e.g. BigQuery, Apache Iceberg, Parquet).
Experience with data visualization tools (e.g., Tableau, Power BI, Plotly, Streamlit).
Experience with biological image segmentation and analysis like segmenting cells or tissue subtypes and quantifying features from microscopy images — is a strong plus.
Knowledge of biomedical data standards, or prior experience with scientific or laboratory data systems.
Familiarity with machine learning, REST APIs, or DevOps and containerization technologies (e.g., Docker).

Responsibilities

Design, develop, and maintain scalable data pipelines and ETL processes to support data integration across our laboratory, instrument, and research systems.
Build automation to register lab instruments and pipeline outputs into our electronic lab notebook (ELN) and data warehouse, with validation and error handling.
Collaborate with data scientists, analysts, and research teams to define data requirements and deliver robust data solutions.
Model and transform data into clean, queryable tables and help evaluate modern data lake/warehouse storage approaches.
Develop dashboards and visualizations that turn pipeline output into actionable information for scientists and leadership.
Prototype and evaluate an image-analysis pipeline for high-content imaging data, benchmarking segmentation and classification approaches against manual results.
Implement data-quality checks and best practices to ensure data integrity, reliability, and reproducibility.
Monitor data pipelines, troubleshoot issues, and implement solutions to resolve data-related problems.
Develop and maintain comprehensive documentation for data processes, workflows, and infrastructure.