Data Engineering Lead

📋 Description

• Own the Data Platform Roadmap: Set technical direction and deliver high-leverage improvements across reliability, cost, and scale.
• Deliver customer-facing APIs & Feeds: Design and deliver API-backed feeds and enrichment pipelines.
• Level Up Orchestration in Dagster: Build asset-based pipelines, sensors, and IO managers; define patterns for incremental jobs, full refreshes, and reverse ETL.
• Make ingestion boring: Scale ingestion across Airbyte OSS and DLT; handle schema drift, health, rate limits, retries, checkpointing.
• Strengthen BigQuery foundations: Manage partitioning, clustering, and query performance guardrails.
• Raise data quality & observability: Implement freshness SLOs, automated checks, provenance, and alerting; ship runbooks and remediation where possible.

🎯 Requirements

• Hands-on Data Engineering Leader with end-to-end production data platform ownership.
• Dagster expertise: asset-based orchestration in production.
• Warehouse & SQL depth: advanced BigQuery skills and query optimisation.
• Ingestion reality: operated Airbyte or similar; robust ingestion patterns and schema evolution.
• Production API & feeds experience: shipped customer-facing APIs or feeds with SLAs and monitoring.
• Python & engineering rigor: clean Python with typing, tests, CI and linting.

🎁 Benefits

• Competitive salary (top end of market)
• Equity options
• Pension: min 4% contributions with 9fin matching up to 7%
• Private medical insurance
• Paid sick leave with income protection
• Hybrid working; sabbatical after 5 years; enhanced parental leave