Lead backend and data-platform architecture while remaining hands-on with Java production code. Design and operate distributed systems for event ingestion, analytical querying, data processing, and low-latency serving. Work with ClickHouse, BigQuery, Bigtable, Kafka, Redis, GCP, and Dataflow to solve scalability, reliability, performance, and data-correctness challenges. Set technical direction, review designs, mentor engineers, and guide platform convergence across Wingify and AB Tasty.
About the Role
The Engineering Landscape
What You'll DoArchitecture & System Design
What We're Looking For
Nice to Have
Core Skills
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 DoArchitecture & 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.
- 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.
- Own critical systems through design, implementation, deployment, observability, and operation.
- Set technical direction for a platform area or major engineering workstream.
- Break ambiguous product and platform requirements into clear technical designs and execution plans.
- Review architecture and designs from other engineers and challenge assumptions constructively.
- Establish engineering practices around reliability, scalability, observability, performance, and maintainability.
- Mentor SSE-1/SSE-2 engineers and help them grow their system-design and production-engineering capabilities.
- Partner closely with Product, Engineering, Data, and Infrastructure teams.
- Influence architecture beyond your immediate projects without requiring formal people-management authority.
What We're Looking For
- 6+ years of hands-on backend/software engineering experience, with substantial experience building distributed or data-intensive systems.
- Demonstrated ownership of architecture and system design for production systems at meaningful scale.
- Strong hands-on Java experience, including modern Java and JVM backend systems.
- Strong experience designing systems around analytical databases, data warehouses, and/or large-scale non-relational stores.
- Deep understanding of data modelling, partitioning, indexing, clustering, query execution, caching, concurrency, and performance optimisation.
- Strong SQL and analytical-querying experience.
- Experience designing and operating streaming/event-driven architectures, ideally using Kafka or equivalent technologies.
- Experience building batch and/or streaming data pipelines at scale.
- Strong cloud engineering experience; GCP is preferred.
- Experience operating production systems with clear SLOs, observability, failure handling, and performance requirements.
- Strong debugging ability across applications, distributed systems, databases, pipelines, and infrastructure.
- Experience mentoring senior engineers, reviewing technical designs, and influencing architecture.
- Ability to balance long-term platform architecture with pragmatic delivery.
Nice to Have
- Deep production experience with ClickHouse, including schema design, MergeTree engines, partitioning, sorting keys, query optimisation, replication, and performance tuning.
- BigQuery and Bigtable at significant production scale.
- Apache Beam / Dataflow.
- Snowflake or warehouse-native compute architectures.
- Go, Vert.x, or other high-performance backend technologies.
- Experience handling billions of events and/or TB–PB scale analytical datasets.
- Experience with experimentation platforms, A/B testing, funnels, segmentation, identity resolution, cohorts, or behavioural analytics.
- Kubernetes, Docker, CI/CD, Prometheus, Grafana, or GCP Cloud Monitoring.
Core Skills
Java · System Design · Distributed Systems · Data Platform · ClickHouse · SQL · BigQuery · Bigtable · Kafka · Redis · GCP · Pub/Sub · Dataflow · ETL · Microservices · Technical Leadership
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