Our mission is to be the catalyst for massive, measurable, data-informed healthcare improvement through:
Data: integrate data in a flexible, open & scalable platform to power healthcare’s digital transformation
Analytics: deliver analytic applications & services that generate insight on how to measurably improve
Expertise: provide clinical, financial & operational experts who enable & accelerate improvement
Engagement: attract, develop and retain world-class team members by being a best place to work
Location: Cambridge, MA (preferred) or SLC, UT (with frequent/extended travel to Cambridge)
The Data Engineering Manager for the Life Sciences Business will be instrumental to the successful transformation of healthcare by building a data platform that helps bridge the gap between providers and industry, including pharma, biotech, and digital therapeutics companies. The incumbent will be responsible for data acquisition and management activities across the continuum of data; including those from provider environment, 3rd party data providers, and life sciences clients integrating these into a multi-source data ecosystem. Fundamental to these relationships is a robust, standardized, agile, and performant data ecosystem that allows multiple stakeholders to interrogate big datasets. Beyond managing and growing a data engineering and architecture function, the incumbent should be prepared to for the majority of their time to be that of a hands-on contributor, contributing directly to the acquisition and harmonization of data, particularly in the early stages of the team.
This role is a great fit for someone who has significant data management and acquisition experience in the healthcare space. The work that the Data Engineering Manager oversees will contribute significantly to the mission of accelerating clinical innovation and precision medicine through novel Life Sciences partnerships.
Duties & Responsibilities
Oversee the implementation of data pipelines from multiple sources, including healthcare providers and 3rd party data providers to ensure Life Sciences use cases are met
Utilize tools, technology, and best practices to track and report on data health, data availability over time, statistics across data elements, and data roadmap to Life Sciences leadership and stakeholders
Ensure that data feeds within Health Catalyst provider environments improve consistently over time, both in breadth and depth (e.g., contribute to adding notes as a standard available data type)
Work with Life Sciences colleagues, including via a data engineering stakeholder body, to understand data engineering priorities that will enable use cases such as machine learning, precision oncology, pragmatic clinical trials, and more.
Collaborate with Technical Directors and Data Engineers deployed to each provider site to align on priorities and approach for contributing to data acquisition process.
Communicate project plan to client teams, including discussing the benefits of a homogeneous and extended set of data elements, and bringing in colleagues across Life Sciences and other DOS Mart product leads as appropriate to communicate value proposition.
Verify that Life Sciences data environment meets all regulatory requirements, including audit logs, data provenance, data documentation, de-identification, and data governance.
Work closely with Life Sciences to track and update colleagues on progress of building out data marts across a wide variety of source systems and ensure the availability of data for Life Sciences analytics and data science purposes.
Applied technical experience with: SQL, ETL development, database structures, data modeling, hosted solutions.
Strong mindset of a people first culture with ability to put this into practice by helping retain and grow team professionally while enabling staff to execute at an elite level of performance
Excellent troubleshooting and problem-solving skills with being able to dig deeper to identify SQL Server/Azure performance issues and root cause the issue.
Must have strong understanding of data warehousing and analytic principles and possess the ability to explain general data warehousing concepts to technical and non-technical people.
Strong project management capabilities, with the ability to engage with and follow-up with healthcare clients and solicit information and feedback as required.
Exposure to data management technologies including SQL Databases, data warehouses, data lakes, NoSQL, Hadoop
Experience building solutions for handling unstructured data such as notes, imaging data, and raw genomic data such as BAM files
Strong experience with Extract, Transform, and Load (ETL) processes and concepts. Familiarity with multiple ETL applications is a bonus.
Strong computational skills via SQL, Python, etc.
Knowledge of healthcare-related ontologies/terminologies (ICD, LOINC, RxNorm, etc.)
Experience working with cloud technologies (AWS, Azure, Google) strongly preferred
Must have excellent verbal and written communication
Education & Relevant Experience
BS in Computer Science, Health Informatics, or related field
6+ years of experience working in a data engineering role
3+ years of experience with clinical/healthcare data
1+ years of experience managing a data engineering team