Data Engineer

You will be a senior engineer on the team that owns the real-time data platform. The platform turns operational events (orders, driver locations, geofence transitions, shifts, MQTT session events) into live analytics, routing inputs, and warehoused data across Postgres/TimescaleDB, ClickHouse, and BigQuery. You will own the platform end-to-end: design, implementation, deployment, and production operation of the streaming jobs, CDC pipelines, Kafka Connect bridges, and downstream sinks that move this data.

Responsibilities

— Designing, implementing, and operating stateful Apache Flink streaming pipelines: keyed state, windowing, watermarks, timers, side outputs, custom sources/sinks.

— Designing, developing, deploying, and maintaining Change Data Capture (CDC) pipelines using Flink CDC or Debezium, moving operational database changes into the streaming platform with correct snapshot/incremental handling, schema evolution, and downstream idempotency.

— Building and operating Kafka and Kafka Connect pipelines: topic and partition design, source/sink connectors in distributed mode, schema and converter management, and deadletter routing.

— Owning the path from Kafka → Flink → Postgres / TimescaleDB / ClickHouse / BigQuery, including schema design, idempotency strategy, batch tuning, and observability.

— Diagnosing and fixing production issues: checkpoint failures, backpressure, state growth, sink slowness, autoscaler oscillation, restart loops.

— Hardening the platform: delivery guarantees, watermarks, DLQ handling, schema migrations, alerting coverage. * Code reviews and mentoring mid-level engineers.

— Contributing to the deployment side: Helm charts, ArgoCD applications, GKE configuration, Grafana dashboards, Prometheus alert rules.

— Influencing direction: state backend choices, schema migrations, when a pipeline needs to be split or rebuilt.

Requirements

— 5+ years of professional software/data engineering experience, with strong Java expertise.

— Production experience with Apache Flink and stateful real-time streaming pipelines.

— Strong Apache Kafka experience, including Kafka Connect, consumer groups, partitions, delivery guarantees, and schema management.

— Hands-on CDC experience using Debezium or Flink CDC.

— Experience designing and operating Kafka → Flink → database/data warehouse pipelines in production.

— Strong understanding of PostgreSQL and experience with at least one analytical database such as ClickHouse or BigQuery.

— Experience with Kubernetes and deploying/operating production data workloads.

— Proven ability to troubleshoot and optimize production streaming systems—backpressure, checkpoint failures, state growth, latency, lag, and sink performance.

— Strong understanding of data consistency, idempotency, schema evolution, and observability.

— Ability to work independently and own a data platform component end-to-end, from design through production operation.

Will be a plus

— Experience with TimescaleDB, hypertables, and time-series data.

— Experience with PostGIS and geospatial/spatial query optimization.

— Deep ClickHouse performance tuning, including MergeTree and partitioning strategies.

— Strong BigQuery optimization and data modeling experience.

— Experience with Flink Kubernetes Operator and Flink autoscaler tuning.

— Experience with ArgoCD, Helm, GKE, Prometheus, and Grafana.

— Experience designing high-throughput, low-latency real-time systems at scale.

— Experience with MQTT or IoT/event-driven systems.

— Knowledge of Kafka Schema Registry, Avro/Protobuf, and advanced schema evolution.

— Experience mentoring engineers and leading technical decisions around streaming architecture.

— Experience with routing, logistics, delivery, mobility, or location-based platforms would be particularly relevant.

What we offer

— 20 days of paid vacation, 5 sick days, and public holidays.

— Flexible schedule with a high level of autonomy.

— Opportunity to influence product and technical decisions.

— Professional growth and learning opportunities.

— Comfortable working environment with a supportive team.

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