5 days ago
Helsinki, Finland or Berlin, GermanySenior
Responsibilities
- Design and build platform services, tools, and workflows for contract-driven data publishing and consumption.
- Build the production path for PostgreSQL publishing tables, Debezium CDC, Kafka topics, and DataHub catalog registration.
- Create code-reviewed and reconciled workflows for contracts, schemas, ownership, lifecycle, compatibility, policies, and runtime state.
- Develop tooling that provides product engineers with fast feedback before publishing or changing data products.
- Define data-product models, publishing contracts, schema evolution, deletion semantics, access policies, lineage, and cost attribution.
- Operate and improve CDC runtimes, including Kubernetes workloads, isolation, offsets, schema history, heartbeats, signals, lag visibility, replay, resnapshotting, and recovery.
- Integrate platform metadata into DataHub for discovery, ownership, lineage, and impact analysis.
- Collaborate with product, infrastructure, data engineering, analytics, and AI/ML teams to improve shared-data workflows.
Requirements
- Strong experience building and operating production software systems, preferably in platform, infrastructure, backend, or data-intensive environments.
- Deep understanding of distributed-systems trade-offs including reliability, idempotency, replay, eventual consistency, compatibility, ownership boundaries, and operational failure modes.
- Practical experience with PostgreSQL or other relational databases, including schema design, migrations, transactions, replication, or operational performance.
- Experience with Kafka, event streaming, CDC, Debezium, or adjacent data-movement technologies.
- Experience building software used by other engineers, such as CLIs, internal platforms, control planes, automation, CI validation, developer tooling, or self-service workflows.
- Familiarity with Kubernetes and cloud or infrastructure platforms, including runtime isolation, deployment, observability, and operational ownership.
- Ability to turn ambiguous architectural direction into practical increments and deliver useful production systems.
- Clear written and spoken communication in English.
- Useful but non-required experience includes DataHub or other data catalogs, lineage or governance systems, Apache Iceberg, S3, BigQuery, ClickHouse, GitHub Actions, policy-as-code, infrastructure-as-code, controllers, operators, data contracts, schema registries, Protobuf, Avro, JSON Schema, compatibility checking, field-level metadata, contract testing, analytics, AI/ML, feature-store-style access patterns, and JVM languages or Python, TypeScript, Go, or Ruby.
Benefits
- Inclusive global culture with trust, transparency, feedback, and respect for different perspectives.
- Global impact through technology used by major brands in digital advertising.
- Wellbeing support, paid holidays, family leave, and sustainable ways of working.
- Equity options, performance-based rewards, competitive compensation, and career development opportunities.
- Flexible hybrid workplace with three days per week in the office.
Tech Stack
Categories
BackendData Engineering
