Engineer, Data and AI Governance

EchoStar•Centennial, CO

16h•Onsite

About The Position

The Data & AI Governance engineer bridges the gap between high-level data governance policies and actual code execution. Working directly within Line of Business (LOB) delivery pods, you will act as the working-level governance partner. You are responsible for the technical implementation of data and AI governance, specifically leveraging but not limited to the Databricks (Unity Catalog) & Snowflake (Horizon Catalog) ecosystems to ensure the delivery of high-quality, safe, and compliant data products. Rather than acting as a traditional auditor, you will "shift left" by integrating automated quality gates and lineage mapping directly into the development lifecycle, serving as the first line of defense for data and AI model safety.

Requirements

Python, Infrastructure as Code (Terraform), and workflow orchestration tools
Cloud platforms, data catalogs, lineage tracking, and access management
Hands-on experience managing governance features in Databricks & Snowflake for cataloging, fine-grained access control, and end-to-end lineage tracking) and Databricks Genie
Strong understanding of Lakehouse architectures, Delta Lake, Glue and Horizon Catalog as well as data pipelines to inspect, and validate underlying data quality.
Proven ability to translate high-level compliance policies (e.g., data privacy, security classifications) into concrete technical designs and configuration rules
Strong understanding of "shift-left" governance - integrating quality, compliance, and risk checks directly into the early stages of the software/data development lifecycle rather than treating them as a final gate
Comfort operating in fast-paced, pod-based agile environments (Sprints, Stand-ups, Retrospectives) while maintaining an uncompromising focus on "Quality Gates"
Strong analytical skills to evaluate data/AI use cases, distinguish between varying risk levels in real-time, and apply proportional governance controls
Bachelor’s Degree in Computer Science, Data Engineering, Information Systems, or a related technical field
2-4 years of experience in Data Engineering, Data Analyst, Product Management or Technical Consulting with an emphasis on data management or governance
Must have at least 2 years of experience with: Databricks (Unity Catalog) and/or Snowflake (Horizon Catalog) governance administration
SQL, Python, Infrastructure as Code (Terraform), and workflow orchestration tools.
Implementation of "shift-left" automated data quality, privacy, and risk governance controls

Responsibilities

Partner with cross-functional teams to implement Data & AI Governance policies and standards as an overarching Governance Layer on Databricks / Snowflake & other Data Platforms
Serve as the dedicated governance and technical data quality resource within agile delivery pods. Actively participate in stand-ups, sprint planning, and retrospectives to detect compliance and quality risks early, preventing deployment bottlenecks
Manage the initial intake and classification of new data and AI use cases. Perform rapid risk assessments and "T-shirt sizing" to determine the appropriate level of scrutiny, ensuring low-risk initiatives move to production at high velocity while high-risk models receive robust validation
Translate complex corporate governance requirements, data classification rules, and testing evidence mandates into clear, actionable technical instructions for delivery teams. Bridge the communication gap between business stakeholders and technical engineering pods
Monitor the practical performance of governance controls within active pods. Partner with leadership to identify friction points, reduce administrative overhead, and continuously automate the "Governance Engine" to accelerate delivery cycles
Own the build-out of automated governance monitoring and observability — including statistical distribution, variance, and drift checks across Bronze/Silver/Gold data layers — leveraging SQL/Python engineering to deliver scalable, repeatable quality assurance at the platform level