Head of Data Engineering

Raise is building an AI-native loyalty platform and is hiring a Head of Data Engineering to own the architecture, delivery and operation of its data foundation and supporting data products. The role focuses on reliable data systems for loyalty operations, AI recommendations and measurement, working directly with the CTO and product stakeholders.

Responsibilities:

• Architecture and delivery. Own data architecture decisions and engineering standards in partnership with the CTO. Translate priorities into practical designs, implementation plans and production code, with clear tradeoffs for reliability, performance and cost
• Pipelines and ingestion. Build and maintain reliable connectors for payment platforms (such as Stripe and Braintree), CRMs, analytics tools and operational databases. Standardize data contracts, monitoring, retries and replay, using APIs, webhooks, CDC, streaming or batch as appropriate
• Data quality and reliability. Handle updates, duplicates, late-arriving events, backfills and recovery, with automated quality checks and documented operating procedures. Meet agreed targets for correctness, freshness, latency and cost
• Trusted datasets. Model customers, identities, orders, returns and promotion activity with clear definitions, source lineage and reconciliation to operational and financial systems
• Reliable data foundations for analytics, experimentation and AI-powered products. Provide governed metrics and data interfaces that engineering, product, analytics and AI systems can depend on
• Security and access. Enforce data isolation and least-privilege access at service and data boundaries. Implement PII handling, auditability, retention and deletion

Requirements:

• 8+ years of relevant data engineering or data platform experience, with a track record of designing, building and operating production systems
• You actively write code, troubleshoot production problems and ship improvements
• At least 2 years owning a production data platform, including architecture decisions, implementation and operational reliability
• Comfortable working independently, taking responsibility for delivery and explaining technical tradeoffs
• Production experience with materialized views, data modeling, query performance and mutable or late-arriving data
• Strong SQL and Python or equivalent programming skills
• Experience integrating payments, CRM, analytics and operational database sources, including batch and streaming ingestion, CDC, API integrations, automated tests, observability, incident recovery and source-to-target reconciliation
• Experience delivering tenant-aware data access and sensitive-data controls
• Able to agree practical tradeoffs with engineering, product and finance
• Commerce, payments or loyalty data; dbt or similar transformation tooling; experiment instrumentation; identity resolution