Data Engineering and Platform Manager

About the role

The Data Engineering and Platform Manager is the senior hands-on leader of the analytical data foundation on Azure and Databricks, reporting to the Chief Data and Analytics Officer within the IDEA department. The role manages two Team Leads and four Analysts across Data Platform Engineering and Data Integration & Governance, setting architecture and engineering standards and staying technically engaged in high-impact work.

Key responsibilities

• Manage, coach and develop two Team Leads and four Analysts, set priorities, allocate capacity and remove blockers.
• Own the platform roadmap and resource plan, including hiring, performance assessment and succession planning.
• Oversee data ingestion, transformation, orchestration, storage and delivery, and maintain availability, performance, monitoring, scalability and cost discipline.
• Define data models, schemas, freshness and performance requirements from business endpoints and product needs.
• Set standards for data architecture, master/reference data, testing, deployment, documentation, lineage, access, retention and change control.
• Resolve material data-service issues and recurring control weaknesses with source owners and technical partners.

Required profile

• 12+ years of progressive experience in data engineering, data platforms or data architecture, including at least 5 years of people leadership and leading Team Leads or senior technical staff.
• Demonstrated success building, scaling or modernizing a production data platform, with recent hands-on technical delivery.
• Experience designing curated or gold-layer datasets from downstream product needs, optimizing large datasets, integrating data from operational systems and vendors, and establishing data governance.
• Preferred: lending or financial services, business-user support and data reconciliation experience.

Required skills

• SQL, dimensional and analytical data modeling, ETL/ELT, orchestration, APIs, cloud storage and compute, automated testing, CI/CD, observability and incident management.
• Strong practical ability to deliver in Azure and Databricks, including lakehouse patterns, query and model optimization, partitioning, caching and cost optimization.

What we offer

• Compensation in USD.
• Paid time off (PTO).
• Fully remote work environment.