AI and Data Governance Engineer

We are a Firm where people truly believe in what they do and strive to achieve the highest standards of performance and success. This position may be based at the Firm's Global Operations Center in Tampa, Florida, or at one of the Firm's offices in D.C, Dallas, or Atlanta. General Description: We are seeking an AI and Data Governance Engineer to join our team. The AI and Data Governance (AIDG) Engineer is responsible for implementing, configuring, and maintaining the technology stack that powers the AI and data governance program. This includes the data catalog (Atlan), data quality & observability platform (Monte Carlo), and tools and initiatives such as master data management and AI governance solutions. This role works closely within the AIDG Team, as well as the broader Data Strategy and Knowledge & Innovation teams, to ensure that data is discoverable, trustworthy, and governed throughout its lifecycle. Key Responsibilities and Essential Job Functions: Platform Ownership & Administration Serve as primary administrator for: Data catalog (Atlan): users, roles, workspaces, integrations, policies Data quality / observability tool (Monte Carlo): monitors, alerts, integrations Tools and initiatives like MDM and AI governance / model registry platforms Manage configuration, upgrades, and maintenance in partnership with vendors. Monitor system health, performance, and usage. Drive improvements and automation where possible. Coordinate closely with IT on system administration. Integration & Automation Integrate governance tools with key data platforms (e.g., data warehouse/lake, BI tools, orchestration platforms, source systems). Develop and maintain pipelines to: Synchronize metadata into the data catalog. Push incident/alert data from observability tools into ticketing/incident systems. Synchronize ownership, classifications, and tags across systems. Automate repetitive tasks (user provisioning, role assignments, metadata sync jobs, etc.) where possible. Metadata Management & Lineage Implement and maintain technical and business metadata in Atlan. Configure and validate data lineage across pipelines, data stores, and BI layers. Advise on metamodel design for business glossaries, domains, and classifications. Establish best practices for naming conventions, tagging, and documentation within the tools. Data Quality & Observability Configure and optimize Monte Carlo for: Freshness, volume, and schema checks Custom rule-based and anomaly-based quality monitors Incident routing, severity, and escalation rules Partner with data engineering and AIDG analysts to embed data quality checks into critical pipelines. Track, report, and help reduce data incidents, broken pipelines, and recurring quality issues. Reference Data and User Enablement Help define how golden records, reference data, and crosswalks are surfaced in the catalog and monitored in the DQ tool. Ensure consistent identifiers, hierarchies, and mappings across systems. Pr