Lead Engineer - Backend (Data Platform)

About the Role We are looking for a Lead Engineer — Backend / Data Platform to provide technical leadership for backend and data-intensive systems powering analytics, reporting, experimentation, and behavioural insights across Wingify <> AB Tasty. This is a hands-on technical leadership role , not an engineering management position. You will continue to design systems and write production code , while also owning architecture and technical direction for significant workstreams. You will work across Java, ClickHouse, BigQuery, Bigtable, Redis, Kafka, and GCP , solving problems spanning event ingestion, distributed processing, query engines, analytical storage, low-latency serving, and reporting. A key part of the role is helping us evolve two mature analytics platforms toward a more unified data foundation without compromising the reliability of systems already serving production customers. The Engineering Landscape Our production data platform includes: ClickHouse — self-hosted and ClickHouse Cloud for high-volume analytics and SaaS reporting BigQuery — large-scale analytics and data processing Bigtable — low-latency NoSQL serving Redis — caching, queues, and distributed coordination Kafka — high-volume real-time event streaming GCP — GCS, Pub/Sub, Dataflow, IAM, Secret Manager, GKE and VMs Java — Spring Boot and JVM-based backend services Apache Beam / Dataflow — distributed event and batch processing Go — adjacent SQL and reporting services Alongside the existing platform, we are building capabilities around: Warehouse-native experiment computation in customer Snowflake/BigQuery environments Cross-platform visitor profiles and identity First-party cohorts and saved audiences Unified metrics across internal and customer warehouses Converging Wingify and AB Tasty analytics onto a common data foundation What You'll Do Architecture & System Design Own the technical architecture and design of significant backend/data-platform workstreams. Design distributed systems for high-volume event ingestion, analytical querying, data processing, and low-latency serving . Make architectural decisions around data modelling, storage engines, partitioning, query patterns, caching, streaming, reliability, and cost . Evaluate trade-offs across ClickHouse, BigQuery, Bigtable, Redis, Kafka, and other technologies based on workload characteristics. Drive designs that can evolve as the Wingify and AB Tasty platforms converge. Hands-on Engineering Remain hands-on with Java and production backend code . Build and evolve backend services, query engines, APIs, data pipelines, and distributed processing systems. Write and optimise complex analytical SQL and troubleshoot performance bottlenecks. Solve difficult production problems involving slow queries, data correctness, pipeline failures, latency, throughput, and infrastructure . Work with Kafka, Pub/Sub, Dataflow, GCS, ClickHouse, BigQuery, Bigtable, and Redis at production scale. …