Principal Data Engineer, Data Platform

A Place for Mom is building the next generation of intelligent, scalable platforms that connect families, providers, and advisors through data- and AI-driven experiences. They are seeking a Principal Data Engineer to define and evolve their enterprise data platform strategy, ensuring effective data governance and enabling self-service analytics across the organization.

Responsibilities:

• Define and evolve the technical vision and roadmap for APFM's Databricks platform and broader data ecosystem
• Drive the evolution of APFM's federated data operating model, balancing domain ownership with enterprise governance and standards
• Partner with Analytics Engineering and business stakeholders to evolve the semantic layer, ensuring business definitions, metrics, and dimensions remain consistent, discoverable, and trusted
• Establish standards for metadata management, lineage, discoverability, stewardship, and data quality across the organization
• Drive development of reusable data products and shared platform capabilities that enable self-service analytics at scale
• Lead adoption and governance of Databricks capabilities including Delta Lake, Unity Catalog, Workflows, AI/BI Genie, MLflow, Vector Search, and related platform services
• Partner closely with AI and Machine Learning teams to establish scalable operational patterns for model development, deployment, monitoring, and governance
• Guide technical decision-making across multiple teams and domains, helping align platform investments with business outcomes
• Mentor engineers across the organization and help elevate technical capabilities and engineering excellence

Requirements:

• 10+ years of experience in data engineering, data platform architecture, governance, or related disciplines
• Deep expertise designing and operating enterprise-scale Databricks Lakehouse platforms
• Extensive experience with Spark, Delta Lake, Unity Catalog, Databricks Workflows, and platform governance capabilities
• Strong proficiency in SQL, Python, and PySpark, with experience building and optimizing data processing workloads on Databricks
• Experience designing and supporting semantic layers, metrics governance, and self-service analytics capabilities
• Strong understanding of governance, metadata management, lineage, observability, security, and reliability engineering principles