• Build, optimize, and maintain data pipelines • Work closely with data scientists, analysts, and engineers • Design scalable and reliable data architectures • Collaborate across teams to implement data solutions

• Provide timely, well-documented responses to data questions from stakeholders across Engineering, Marketing, Business, Data Science, and Analytics, escalating when appropriate and keeping requesters informed. • Take on well-scoped, small data modeling requests in our warehouse: update or add dbt models and tests, write clear model documentation, and open PRs with thoughtful descriptions and checks. • Support the health of our data platform by pairing with the on-call engineer to monitor job runs and alerts, triage issues, and execute playbooks; escalate quickly when outside scope. • Proactively monitor nightly and hourly pipelines (e.g., Airflow DAGs, dbt Cloud runs, AWS DMS replication tasks) and remediate common failures (retries, backfills, simple config fixes) under guidance. • Help maintain data reliability by responding to Monte Carlo observability alerts, validating anomalies, and creating or refining data quality tests. • Partner with engineers to simplify and automate routine remediation steps; contribute small improvements that make our pipelines more robust and observable. • Document what you learn: improve runbooks, add troubleshooting steps to our internal knowledge base, and keep tickets updated with clear status and outcomes.

• Review and assess GMCB's existing Data Governance Charter; deliver charter improvement recommendations covering decision rights, policies, stewardship models, and governance workflows (Deliverable B1) • Conduct a Metadata and Stewardship Standards Assessment covering data dictionaries, metadata practices, stewardship assignments, and data collection standards (Deliverable B2) • Develop the Updated Governance Standards Package including revised charter, RACI matrix, refined stewardship roles, metadata standards, and Data Governance Playbook v1.0 (Deliverable B3) • Author the comprehensive Data Governance Playbook covering governance framework, data asset profiles (VHCURES, VUHDDS, ASSR), data quality standards, and stewardship procedures • Design and deploy the Governance Dashboard Suite in Power BI: Governance Activity, Compliance, Data Quality, and Stewardship Performance dashboards (Deliverable B4) • Develop and deliver Governance Training & Enablement Materials for GMCB Data Stewards and leadership (Deliverable B5) • Design integration patterns between Azure Databricks, ADO, and Power BI to support automated data quality monitoring and governance compliance tracking • Establish data quality standards, lineage tracking, and metadata governance aligned with HIPAA requirements for regulated health datasets • Define governance workflows, approval triggers, and policy enforcement mechanisms using Power Automate and ADO pipelines • Collaborate with the DevOps Engineer and Agile Coach to embed governance checkpoints into sprint workflows and CI/CD pipelines

• Build and maintain production quality data pipelines between operational systems and BigQuery (ingress and egress). • Implement data quality and freshness checks and monitoring processes to ensure data accuracy and consistency. • Maintain and contribute to our ingestion framework that leverages various purpose-built data load tool (dlt) connectors. • Create and maintain comprehensive documentation for data engineering processes, systems, and workflows • Maintain observability and monitoring of our internal data pipelines. • Troubleshoot and resolve data pipeline issues to ensure downstream data availability. • Contribute to our dbt systems by making sure the source and staging layers align with our standards, are efficient, cost-effective, and highly available. • Participate in the investigation and implementation of event-driven data movement and transformation processes. • Participate in the investigation and implementation of analytic data storage/table formats (e.g. Apache Iceberg)