Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Databricks Data Governance Engineer based in the United States.
This is a senior technical role focused on designing and implementing secure, scalable data access governance across a Databricks Lakehouse environment. You will serve as a technical owner for the data access control model, shaping architecture, engineering standards, and security controls. The position combines hands-on software engineering with data platform security, identity governance, infrastructure automation, and compliance. You will work closely with data engineering, platform engineering, workspace administrators, and enterprise stakeholders. A key focus will be translating regulatory and security requirements into practical controls that can operate at scale. The role offers the opportunity to establish strong governance foundations while directly implementing modern Databricks security capabilities.
Accountabilities
<ul>
<li>Lead the design and implementation of role-based access control (RBAC) and attribute-based access control (ABAC) within Databricks Unity Catalog.</li>
<li>Define scalable data access models, including data structures, permissions, tagging standards, and governance patterns.</li>
<li>Design and implement security architecture using dynamic views, row-level security, column-level filtering, and data masking.</li>
<li>Develop identity governance strategies for Databricks, including service principals, workload identities, SCIM, and integrations with enterprise identity providers.</li>
<li>Translate regulatory, contractual, security, and compliance requirements into practical technical controls across the data platform.</li>
<li>Establish and maintain data classification standards and tagging frameworks that support scalable and auditable access management.</li>
<li>Implement Databricks grants, catalogs, tags, permissions, and policies as code using Terraform and/or Databricks Asset Bundles.</li>
<li>Apply infrastructure-as-code practices to support version control, repeatability, automation, and audit readiness.</li>
<li>Partner with workspace administrators and platform engineers to align workspace, compute, secrets, and network controls with the overall data access strategy.</li>
<li>Build governance guardrails, reusable templates, and streamlined workflows that allow data engineers to manage appropriate access while maintaining strong security controls.</li>
<li>Use Python and SQL to develop automation, monitoring, and compliance capabilities.</li>
<li>Provide technical leadership and hands-on implementation support as the data governance and security function evolves.</li>
</ul>
Requirements
<ul>
<li>Bachelor’s degree in a relevant discipline with at least 8 years of experience as a Software Engineer, Data Engineer, or similar technical professional focused heavily on data platform security and security automation; alternatively, a Master’s degree with at least 6 years of relevant experience.</li>
<li>At least 2 years of hands-on experience implementing Databricks Unity Catalog security features.</li>
<li>Demonstrated experience designing and implementing RBAC and ABAC models at scale.</li>
<li>Hands-on expertise with Databricks Unity Catalog, grants, dynamic views, row-level filtering, column-level filtering, and data masking.</li>
<li>Strong understanding of identity and federation patterns, including SCIM, service principals, workload identities, and enterprise identity provider integrations such as Entra ID.</li>
<li>Experience applying infrastructure-as-code practices, particularly Terraform, to Databricks access controls, tagging, and policy management.</li>
<li>Proficiency in Python and SQL for automation, monitoring, governance, and compliance activities.</li>
<li>Strong understanding of data platform security, access governance, and scalable security architecture.</li>
<li>Ability to translate complex regulatory and security requirements into clear, implementable technical controls.</li>
<li>Strong collaboration and communication skills, with the ability to work effectively across data engineering, platform engineering, security, and enterprise stakeholder groups.</li>
<li>Ability to obtain a government security clearance.</li>
<li>A Master’s degree is preferred.</li>
<li>Full-time onsite work in Falls Church, Virginia is preferred, although the role also supports full-time telework.</li>
</ul>
Benefits
<ul>
<li>Base salary range of $142,200–$213,200 USD per year.</li>
<li>Potential eligibility for overtime, shift differentials, and discretionary performance-based bonuses, depending on the position.</li>
<li>Health insurance coverage.</li>
<li>Life and disability insurance.</li>
<li>Savings and retirement benefits.</li>
<li>Company-paid holidays.</li>
<li>Paid time off for vacation and/or personal business.</li>
<li>Fully remote/telework option available.</li>
<li>No relocation assistance is provided.</li>
<li>No travel required.</li>
<li>Opportunity to work on large-scale data governance, security, and cloud data platform initiatives.</li>
</ul>
How Jobgether Works
We use an
AI-powered matching process
to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice:
By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Databricks Data Governance Engineer

Databricks Data Governance Engineer

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