IntegriChain | Data Engineer -

Data Engineer

Ambler, PA | Dev / Eng

Job Description
Company Culture


At IntegriChain, we help life sciences manufacturers to get patients on therapy faster and stay on therapy longer through innovative data pipelines and analysis. We are in a unique position to transform healthcare in our country, but we need to build a world class data science infrastructure to do so.

As part of the data services operation team, you will be collaborating with data scientists to build a platform for turning data science insight into production processes. You’ll be bringing your engineering experience and skills to a team trying to bring new actionable insights to our clients based on our rich data warehouse of data that extends over how pharmaceuticals are distributed, paid for, and administered to patients.  You’ll design and implement critical ETLs for making our data ready for data science, create data access libraries, tooling for our data operations, and help turn prototypes into configurable products.


You will:

  • Collaborate with data scientists to make their code efficient and production ready
  • Support and extend our data pipeline orchestration platform
  • Create libraries and infrastructure for use across our data pipelines
  • Create, manage and debug ETL jobs, creating data science ready datasets


We’re looking for:

  • Bachelor’s degree with a major in engineering or science
  • Someone with a strong engineering background and an interest in data
  • Excellent Python skills & real-world experience building production quality, testable, deployable software (3+ years)
  • Experience with data science libraries and tools, e.g. pandas and Jupyter notebooks (2+ years)
  • Extensive experience working with SQL and other data sources (5+ years)
  • Experience with AWS and deploying software on AWS (1+ years)
  • Experience with docker and containerization (1+ years)

It’s a bonus if you have experience with or interest in:

  • Scala and Spark
  • Machine learning & statistics
  • Cloud DevOps (AWS)
  • Airflow or other data pipeline orchestration tools
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