Head of Data Engineering

About Raise Loyalty
Raise is developing an AI-native loyalty platform that helps brands plan, run and measure promotions for first purchases, repeat purchases and reactivation. Brands set goals and budgets, review AI recommendations and approve campaigns. We are making Raise our first customer, with external design partners using the same core in their own customer experiences.
This new product builds on Raise's established commerce, payments and gift card business. Our longer-term roadmap includes a rewards API for personal assistants and commerce agents. You will work directly with the CTO and product stakeholders to turn business needs into reliable data systems.
The role
Own data architecture, technical standards and hands-on delivery at Raise. Your focus is Zenith, Raise's data foundation, and the data products supporting loyalty operations, AI recommendations and measurement. This is an individual contributor role reporting to the CTO, with direct responsibility for designing, building and operating the data platform.
What you will own
• 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.
What you bring
• Hands-on engineering. 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.
• Platform ownership. 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.
• ClickHouse expertise. Production experience with materialized views, data modeling, query performance and mutable or late-arriving data. Strong SQL and Python or equivalent programming skills.
• Integration and reliability. 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.
• Security and collaboration. Experience delivering tenant-aware data access and sensitive-data controls. Able to agree practical tradeoffs with engineering, product and finance.
Useful additional experience
Commerce, payments or loyalty data; dbt or similar transformation tooling; experiment instrumentation; identity resolution.
How we work
You will spend most of your time designing, coding, testing and operating the data platform, and work directly with the CTO to agree priorities and make technical decisions. We start with the data sources that matter most, then expand reusable patterns as demand becomes clear.

Work arrangement
Yes