Surescripts serves the nation through simpler, trusted health intelligence sharing, in order to increase patient safety, lower costs and ensure quality care . We deliver insights at critical points of care for better decisions — from streamlining prior authorizations to delivering comprehensive medication histories to facilitating messages between providers.
Job Summary:
The Data Governance Engineer is part of our Data Trust & Enablement team within the Enterprise Data Platform. This role is central to how we build confidence in our data - across the teams that produce it, the systems that move it, and the stakeholders who depend on it. This position supports the architecture and execution of our enterprise data quality framework, bringing engineering rigor and automation to problems that today rely too heavily on manual discovery and reactive fixes. This role works alongside data engineers, architects, platform engineers, analysts, and governance leads to make data trust a first-class property of how we build and operate our data platform. This is not a documentation-only or policy role. It is an engineering role on a team that believes governance should be automated, observable, and embedded in the development lifecycle.
Responsibilities
Help architect and build the foundational framework that defines what trusted data means at Surescripts across dimensions of completeness, accuracy, freshness, consistency, and fitness for purpose.
Translate abstract data quality concepts into concrete, measurable, automatable rules that can be applied at scale across the medallion architecture.
Develop and maintain data contracts between producing and consuming teams, with tooling that catches violations before they reach downstream systems.
Integrate governance checks into developer workflows so that quality and compliance are default behaviors, not afterthoughts.
Contribute to and extend our metadata platform (data catalog, lineage, tagging) to support discoverability, trust scoring, and impact analysis.
Help design and implement the automated pathway through which a data asset moves from unvalidated to certified, including rule execution, scoring, threshold management, and integration with Collibra for catalog-level certification status.
Make certification a first-class part of the data product delivery lifecycle.
Coach teams on trust and governance standards and help them instrument their pipelines.
Serve as a subject matter expert on governance best practices for data engineers, analysts, and product teams. Advocate for and implement a "trust by design" principle across the platform engineering and data product development workflows.
Help define the organization-wide vocabulary and standards for data trust: what a critical data element is, what certification means, what the difference is between a validated asset and a trusted one.
Partner with the Trust and Enablement leadership to ensure standards are enforced in Collibra and visible to business stakeholders.
Qualifications:
Basic Requirements:
Bachelor’s degree in computer science, engineering, business administration, or related field
2+ years of experience in data engineering, data platform development, or a closely related field with a demonstrated focus on data reliability and observability.
Prior experience with Collibra data quality, Monte Carlo, Great Expectations, or equivalent.
Hands-on experience designing and implementing data validation frameworks, quality rule engines, or observability pipelines, ideally in a cloud-native environment.
Strong SQL skills and experience working with Big Query or a comparable cloud data warehouse at scale.
Experience integrating data trust or quality metadata into a data catalog-Collibra experience is a strong plus.
A platform engineering mindset - focus on systems, frameworks, and reusable patterns, not one-off fixes.
Ability to communicate trust concepts clearly to non-technical stakeholders, including governance teams, product owners,…