Senior Data Governance Engineer at AIT Worldwide Logistics

Job description

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 FinOps 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 control, testing, deployment, and observability in the work this role produces. • Support existing pipelines and troubleshoot platform, access, and data-processing issues in partnership with the broader data engineering team. • Produce clear technical documentation and operational procedures that improve platform sustainability and supportability. • Collaboration & Technical Leadership: • Partner with technology teams, analysts, business stakeholders, data owners, and other subject matter experts to translate requirements into governed, well-documented data. • Contribute to AIT's data governance, security, access-control, retention, lineage, and lifecycle-management standards. • Provide technical leadership, mentoring, and knowledge sharing to teammates working with AIT's data platform. • Communicate complex technical and data-definition concepts clearly to both technical and non-technical audiences. • Proactively identify platform and governance risks, gaps, and opportunities and recommend practical paths forward. • As the data platform function grows, take on additional leadership responsibilities, which may include future direct reports. • Performs other duties as assigned • Complies with all policies and standards • The wage range for this position is $118,330-$177,490 and may vary based on geography as well as relative knowledge, skills, abilities, and experience. Education • High School (required) • Bachelor's Degree Computer Science, Engineering, Information Systems, Data Science, or a related technical field (required) Experience • 5+ years Data governance, data management, analytics engineering, or data platform experience, including hands-on work with modern cloud data technologies (required) • 3+ years Administering or configuring cloud-based data platforms on AWS, including IAM, S3, networking, security, and access management (required) • 3+ years Hands-on Databricks experience, including Unity Catalog administration, permissions, and Delta Lake (required) • 3+ years Developing or maintaining enterprise data dictionaries, metadata, data catalogs, business glossaries, lineage, or related data-governance capabilities (required) • 1+ years Using AI/GenAI-enabled tools, such as Databricks Genie, for data discovery, analytics, engineering, or documentation (preferred) Knowledge, Skills, and Abilities • Strong Communication skills and cross-functional collaboration Databricks administration, including Unity Catalog, permissions, and Delta Lake • AWS platform administration, including IAM, S3, networking, security, and FinOps - Advanced • SQL, Python, and PySpark for data transformation, scripting, and automation - Intermediate • Data modeling, metadata management, data dictionaries, business glossaries, and data catalogs • Databricks Genie and AI-assisted data tooling- Advanced Medium • CI/CD, Git, automation, and Infrastructure as Code such as Terraform • Data governance, data quality, security, and lineage • Access provisioning, permissioning, and identity/entitlement administration • Problem solving, navigating ambiguity, and creating structure • Technical documentation and knowledge sharing • Performance optimization, troubleshooting, and root-cause analysis Licenses and Certifications • - Databricks Certified Data Engineer — Associate (or higher) (required) • - AWS Certified Solutions Architect — Associate (or higher) (preferred) AIT Worldwide Logistics is a global freight forwarder that helps companies grow by expanding access to markets all over the world where they can sell and/or procure their raw materials, components and finished goods. For more than 40 years, the Chicago-based supply chain solutions leader has relied on a consultative approach to build a global network and trusted partnerships in nearly every industry, including aerospace, automotive, consumer retail, energy, food, government, high-tech, industrial, life sciences and marine. Backed by scalable, user-friendly technology, AIT’s flexible business model customizes door-to-door deliveries via sea, air, ground and rail—on time and on budget. With expert teammates staffing more than 150 worldwide locations in Asia, Europe and North America, AIT’s full-service options also include customs clearance, warehouse management and white glove services. AIT Worldwide Logistics is an Equal Opportunity Employer – M/F/Veterans/Disabled. If you are unable to apply online due to a disability, contact Human Resources at 630-766-8300 ext 5218.

Requirements

Must-haves

Join us at AIT, where we believe every day presents an opportunity to make a global impact!
• 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 FinOps 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.
• 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.
• Build and maintain targeted data pipelines and transformations in Databricks using SQL, Python/PySpark, and Delta Lake to support governance, documentation, and reporting needs.

Nice-to-haves

• 1+ years Using AI/GenAI-enabled tools, such as Databricks Genie, for data discovery, analytics, engineering, or documentation (preferred)
• - AWS Certified Solutions Architect — Associate (or higher) (preferred)

Application prep

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