Senior Data Governance Engineer
Listed on 2026-09-07
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IT/Tech
Data Engineering, Information & Knowledge Management
Introduction
Join us at AIT, where we believe every day presents an opportunity to make a global impact!
We’re problem solvers, driven by our curiosity and creativity, in endless pursuit of solutions for our customers. Together, we champion the strength of our global teams. And, as trusted advisors, we go above and beyond, working together in a supportive and collaborative environment to ensure customer satisfaction.
Through the company's continued growth, we challenge ourselves to be better, continuously learning and growing in our dynamic environment. Helping others is at the core of our culture, join us in finding fulfillment by giving back to our local communities as the united team that is AIT. Find out what our people deliver. means when you come move the world with us!
Hear directly from our teammates at AIT Worldwide Logistics and make us the next stop on your career journey.
The Senior Data Governance Engineer, Databricks & AWS is responsible for managing AIT's enterprise data dictionary, metadata, governance standards, and Databricks/AWS configuration, provisioning, and access controls. The role ensures enterprise data is trusted, secure, well-documented, and accessible by strengthening data governance, quality, and compliance practices.
Additionally, the position supports governance initiatives through automation, scripting, and targeted pipeline support, while leveraging AI-enabled tools such as Databricks Genie to enhance data discovery, documentation, and self-service analytics. Working closely with business and technology stakeholders, the role provides technical leadership, mentors teammates, establishes scalable governance standards, and may evolve to include people management responsibilities as AIT's data platform grows.
- Enterprise Data Dictionary, Metadata & Lineage:
Own the development, implementation, and ongoing maintenance of AIT's enterprise data dictionary. Establish consistent definitions, naming standards, metadata, business terminology, and technical documentation for enterprise data assets. Develop and maintain lineage and source-to-target documentation that improves transparency and trust in enterprise data. Partner with business stakeholders, data owners, and subject matter experts to validate definitions and resolve inconsistencies. Integrate data dictionary, metadata, catalog, and governance practices with Unity Catalog, Databricks, and related enterprise tooling.
Drive adoption of common data definitions and make trusted information easier for teammates to discover and understand. Establish the review cadence, change-control process, and ownership model that keep definitions current as the business evolves. - Platform Configuration, Provisioning & Access Management:
Administer Databricks workspace and Unity Catalog configuration, including catalogs, schemas, grants, groups, service principals, and related platform settings. Own user and workload provisioning and permissioning across the platform — onboarding, role and entitlement assignment, periodic access review, and deprovisioning. Administer and secure the AWS environment supporting AIT's Databricks platform, including IAM, S3, networking, connectivity, and permissions. Establish and maintain security, access, resource, and configuration standards, and document them so access decisions are consistent and auditable.
Monitor platform capacity, utilization, and cloud costs, and apply Fin Ops and cost-governance controls for Databricks and associated AWS resources. Partner with infrastructure, security, and technology teams to ensure the platform meets AIT requirements for availability, security, scalability, and operational support. - AI-Enabled Data Discovery & Delivery:
Use Databricks Genie and other approved AI and GenAI capabilities to improve enterprise data discovery, analytics, documentation, and self-service. Configure and curate AI-enabled data experiences that allow users to interact more effectively with governed enterprise data. Ensure the dictionary and metadata layer is structured to support reliable AI-assisted discovery and natural-language querying. Identify opportunities to automate or accelerate documentation and data-management activities through AI-assisted tooling.
Establish appropriate patterns and guardrails for reliable use of AI-enabled data capabilities. Evaluate emerging Databricks and AI capabilities and recommend adoption where they provide measurable business value. - Data Platform Engineering & Automation:
Build and maintain targeted data pipelines and transformations in Databricks using SQL, Python/PySpark, and Delta Lake to support governance, documentation, and reporting needs. Automate recurring platform, provisioning, and documentation tasks through scripting, platform APIs, and Infrastructure as Code such as Terraform. Implement data quality controls, monitoring, and alerting, and drive data reliability issues to resolution. Apply sound engineering practices for source…
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