Senior Data Engineer

Role overview

Build and operate the data infrastructure behind targeting, identity, and measurement products. This is a hands-on senior engineering role focused on dependable pipelines, scalable cloud systems, deployment automation, and the practical delivery of new data sources. The position is remote and based in London, UK, with responsibility for systems that enable reliable data flow and faster engineering delivery.

Responsibilities

- Build, optimize, and run ETL and ELT pipelines, identifying bottlenecks, documenting service expectations, and detecting incidents early. - Integrate new data sources from ingestion through activation, connecting them to targeting and measurement use cases with defined performance goals. - Maintain deployment automation using ArgoCD, automated testing, and monitoring practices that improve release reliability and reduce rollback risk. - Implement identity and targeting approaches that incorporate GDPR and CCPA requirements directly into the data platform. - Make infrastructure and scaling decisions across AWS, EKS, Docker, and Kubernetes, taking operational ownership of the systems delivered. - Produce clear technical documentation, runbooks, design guidance, and decisions that support independent onboarding and operation.

Requirements

- Deep proficiency in Python and Spark for building and tuning large-scale data pipelines and structuring data for efficient processing. - Hands-on Airflow experience for complex workflow orchestration and Apache Iceberg experience for managing tables at scale. - Extensive AWS experience, including EKS, Docker, and Kubernetes, with confidence owning infrastructure deployment and scaling. - Strong CI/CD and observability skills, particularly with ArgoCD, automated test pipelines, and Prometheus. - Familiarity with Snowflake or ClickHouse, including SQL optimization, cost control, and performance tuning. - Working knowledge of identity, privacy, and targeting concepts in advertising technology, including where privacy constraints affect data flows.

Nice to have

- Experience with Kafka, Flink, or another real-time streaming technology. - Familiarity with Aerospike or a comparable low-latency key-value store used in high-throughput systems.