Head of Data

Join our team as the Head of Data, where you will own the company's data platform and lead the Data Platform Engineering team. You will be responsible for the technical direction of the data platform, developing a roadmap that balances business priorities with long-term investments, and implementing platform-wide governance. You will also enable ML & AI workloads and build self-service capabilities for analysts and power users. This role requires strong experience with Databricks or a comparable lakehouse platform, data modeling frameworks, and cloud platforms.

• Ownership of the company's data platform, ensuring data is ingested, processed, governed, and made available reliably and securely for analytics, AI, machine learning, and operational applications.
• Leading the Data Platform Engineering team, accountable for both the team's growth and the platform's operational excellence, and making architectural decisions that keep the platform scalable, secure, and maintainable.
• Developing a roadmap that balances business priorities with long-term platform investments, and implementing platform-wide governance in partnership with Security and Architecture to ensure compliance.
• You think like an architect and work like an engineer: you can set a long-term technical direction and still get into the details of a Spark job or a pipeline that's misbehaving.
• You've led engineering teams before, and you know how to turn a roadmap into shipped, reliable infrastructure.
• You partner naturally with Product, Engineering, Machine Learning, Architecture, Security and business stakeholders, and you bring the same pragmatism to picking battles as you do to picking technology
• Strong experience with Databricks or a comparable lakehouse platform, and with data modeling frameworks such as Kimball dimensional modeling
• Experience with CDC technologies such as Debezium
• Strong knowledge of Apache Spark internals (shuffling, driver vs. executor architecture, lazy evaluation) and experience building reliable, production-grade ELT/ETL pipelines
• 8+ years in Data Engineering or Data Platform roles, including 3+ years leading engineering teams, with experience operating enterprise-scale data platforms in production
• Experience with data catalogs, data masking techniques and data governance platforms (DataHub, Atlan, OpenMetadata)
• Experience implementing Medallion Architecture using a transformation tool such as dbt
• Experience designing architectures that combine batch and streaming processing (e.g. Lambda or Kappa), including checkpointing, state management, exactly-once semantics and watermarking
• Experience with cloud platforms (Azure preferred; AWS or GCP acceptable) and Infrastructure as Code (e.g. Terraform) and CI/CD pipelines