Senior Databricks Governance Engineer

Job Summary

Scientific Games is seeking an experienced Senior Databricks Governance Engineer to design, build, and evolve the governance capabilities supporting our enterprise data platform on Databricks running on AWS.Working closely with the Principal Enterprise Data Architect and Principal Analytics Engineer, this role is responsible for translating governance standards into scalable engineering capabilities that ensure enterprise information is trusted, secure, discoverable, compliant, and consistently managed. The role focuses on implementing metadata management, Unity Catalog, data lineage, access controls, data quality, governance automation, and stewardship capabilities that are embedded directly into engineering workflows.This is a highly hands-on engineering role. The successful candidate is expected to spend the majority of their time designing, building, automating, and optimizing governance capabilities while partnering with engineering teams to ensure governance is implemented consistently across the platform.

Success requires deep expertise in Databricks, Unity Catalog, metadata, lineage, data quality, security, and governance automation, along with the ability to drive engineering excellence through automation, reusable frameworks, and technical leadership.

Scope

Owns the engineering implementation of governance capabilities across the Databricks Lakehouse Platform running on AWS.

Success is measured by:

• Trusted metadata
  • Complete lineage coverage
  • Automated governance and policy enforcement
  • Certified Data Products
  • High data quality
  • Secure information access
  • Governance observability
  • AI-ready trusted information

Job Duties / Key Accountabilities

Unity Catalog Engineering

• Design and manage Unity Catalog structures supporting enterprise governance.
  • Configure catalogs, schemas, external locations, storage credentials, volumes, and secure sharing.
  • Engineer RBAC, ABAC, row filters, column masking, and secure access patterns.
  • Develop reusable governance patterns supporting multiple business domains.

Metadata & Discoverability Engineering

• Build automated metadata collection, synchronization, and enrichment.
  • Engineer technical and business metadata integration.
  • Support enterprise taxonomy and business glossary implementation.
  • Improve discoverability through trusted metadata services.
  • Support certification and promotion of trusted Data Products.

Lineage Engineering

• Design and automate end-to-end lineage.
  • Monitor lineage completeness and accuracy.
  • Enable impact analysis and dependency tracking.

Data Quality Engineering

• Design enterprise data quality frameworks.
  • Develop automated validation, profiling, reconciliation, and monitoring.
  • Implement reusable quality rules and quality scorecards.

Governance Automation

• Develop governance-as-code capabilities.
  • Automate policy enforcement, metadata harvesting, lineage generation, and certification workflows.
  • Develop reusable governance engineering frameworks.

Data Protection Engineering

• Implement data classification and sensitive data tagging.
  • Engineer masking, row-level security, and secure access controls.
  • Partner with Information Security to improve platform protection.

Semantic & AI Governance Enablement

• Implement governance capabilities supporting enterprise semantic assets, certified business metrics, business glossary, and enterprise taxonomy.
  • Ensure semantic assets are governed, discoverable, secured, and reusable across the platform.
  • Implement governance controls supporting AI-ready information and trusted Data Products.
  • Enable trusted consumption of governed information by analytics, enterprise self-service, and AI capabilities.
  • Partner with the Principal Enterprise Data Architect to operationalize governance standards supporting semantic architecture and AI.

Technical Leadership

• Lead technical reviews for governance engineering solutions.
  • Mentor engineers implementing governance capabilities.
  • Partner with the Principal Enterprise Data Architect and Principal Analytics Engineer.
  • Participate in sprint planning, backlog refinement, estimation, and engineering coordination.

Qualifications / Skills / Knowledge

Required

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related discipline.
  • 8+ years designing and building enterprise data engineering solutions.
  • 4+ years hands-on Databricks Lakehouse Platform experience.
  • Strong Unity Catalog, metadata, lineage, and governance engineering experience.
  • Experience implementing RBAC, ABAC, row-level security, column masking, and secure access controls.
  • Experience implementing enterprise data quality engineering and governance automation.
  • Strong SQL, Python, Spark, and AWS experience.
  • Strong software engineering practices including Git, CI/CD, testing, and automation.
  • Experience building reusable engineering frameworks.
  • Excellent troubleshooting, mentoring, and communication skills.

Desired

• Databricks Certified Data Engineer Professional.
  • Experience with Collibra, Atlan, or Alation.
  • Experience with Terraform, Databricks Workflows, and Databricks Asset Bundles.
  • Experience implementing governance in regulated industries.
  • Experience supporting enterprise AI governance.

Authority / Decision Making

Authority To

• Define governance engineering implementation patterns.
  • Establish reusable governance engineering frameworks.
  • Review governance engineering designs.
  • Drive engineering best practices supporting Unity Catalog and governance capabilities.

Requires Approval For

• Governance architecture changes outside approved standards.
  • Platform investments beyond approved strategy.
  • Technology adoption outside approved engineering standards.

Key Contacts

• Head of AI, Data & Infrastructure
  • Principal Enterprise Data Architect
  • Principal Analytics Engineer
  • Platform Engineering
  • Information Security
  • Product Leadership
  • Data Science & ML
  • Databricks
  • AWS

Language Skills

Required: English

Desired: Additional languages considered an asset.

Job Conditions

• Remote position based in India.
  • Regular collaboration with engineering teams across India and North America.
  • Flexible schedule with recurring North America overlap.
  • Occasional international travel (up to 10%).
  • Participation in governance design sessions, architecture reviews, engineering planning, and technical workshops.