Data Governance Engineer

Role Overview Responsible for the technical administration, integration, and optimization of data governance and data quality tools (e.g., Atlan and Monte Carlo). This role ensures these platforms are configured for scalability, integrated with enterprise data ecosystems, and maintained for high availability and performance. The position also supports automation, data quality monitoring, and compliance reporting. Key Responsibilities 1. Platform Engineering & Administration • Configure and maintain Atlan for metadata management, lineage tracking, and governance workflows. • Configure DQ Labs for data quality profiling, rule creation, and monitoring dashboards. • Manage user roles, authentication (SSO, RBAC), and security settings across both platforms. 1. Integration & Automation • Develop and maintain integrations between data sources (databases, data lakes, BI tools). • Automate metadata ingestion and data quality checks using APIs, Python scripts, or ETL frameworks. • Configure connectors for data and BI platforms. 1. Tools Performance & Reliability • Monitor system health and optimize performance. • Apply patches, upgrades, and troubleshoot technical issues. • Implement logging, alerting, and proactive monitoring for governance and quality environments. 1. Technical Support & Issue Resolution • Provide Tier 3 support for platform-related issues. • Debug integration failures and resolve configuration conflicts. • Collaborate with vendors for advanced troubleshooting and roadmap discussions. 1. Security & Compliance • Ensure platforms comply with data privacy and security standards (e.g., GDPR, CCPA). • Implement encryption, access controls, and audit logging. • Support compliance reporting and risk assessments using Atlan governance features and DQ Labs quality metrics. Required Skills & Qualifications • Bachelor’s degree in Computer Science, Data Engineering, or a related field. • Hands-on experience with data governance and data quality tools (e.g., Atlan and DQ Labs), including administration and API integrations. • Familiarity with data catalogs, data lineage, and metadata management. • Strong understanding of data governance principles and data quality frameworks. • Knowledge of Data Mesh strategies and experience in building data products and orchestration.