Data Engineer, Health

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Updated: September 9, 2019
Location: Boston, MA, United States
Job ID: 4307

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We are looking for a data engineer with experience working with healthcare or digital marketing data sets to extend the team’s capabilities by building efficient and scalable frameworks.

This position offers meaningful and challenging work in a team of supportive and bright colleagues. A lot of things will have to be invented and built from scratch. You will not be bored.

Who We Are

The Applied Data Science group is a dynamic, creative team that uses ML technologies to make sense of healthcare data. Syneos Health is an accelerator that helps biopharma companies around the world to research and commercialize new therapies. Our group works with clinical and commercial teams on a broad range of problems.

Typical Projects

  • Evaluate expected contribution of individual channels to the overall campaign performance

  • Analyze data from multiple sources to forecast duration of clinical trial recruitment.

  • Rank physicians’ offices by the availability of nearby public transit options and historical traffic patterns

  • Clean up and deduplicate insurance claims data to measure the time between different health encounters



The data engineer will build and manage databases and establish workflow pipelines that lead to API endpoints in support of data science tasks.

  • Establish ETL for structured and unstructured data sources from internal and external sources

  • Manage code libraries and automate database updates

  • Build and validate new methodologies for dataset QA

  • Manage and create performance/error/analytics systems and processes for QA of all data sets

  • Create dashboards and API data access tools for both technical and business users

  • Introduce best practices for database design, processing, and workflows. Share your knowledge through training others, evaluating new tech, and building our documentation library

Job Requirements

  • Integrating data sources and schema design

  • Querying, troubleshooting, and designing SQL and NoSQL databases

  • Working with common cloud data repositories (AWS) and versioning systems (Git)

  • Building processing pipelines between remote data lakes and local data warehouse

  • Making use of data visualization strategies for data QA to develop internal and end user dashboards (JS libraries and Tableau or similar)

  • Degree in information/library/computer sciences, operations research, physics, engineering field and/or relevant work experience

  • 2-3 years with SQL, NoSQL, Python or similar systems, Spark

  • Independent problem-solving and grit. Willingness to own one’s work, and confidence to push best practices.


    Extra credit

    Full-stack web development skills sufficient for building single-purpose analytical internal web apps


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