Staff Software Engineer - Curated Data
New
J
JobgetherData Infrastructure
Based in GermanyFull-TimeStaff
Salary not disclosed
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Job Details
- Required Skills
- PythonSQLKotlinGoRustData modelingDistributed Systems
Requirements
- Significant experience as a backend software engineer with deep expertise in data systems, or as a data engineer who has developed strong software engineering capabilities.
- Proven track record of building and operating production-grade services, not solely data pipelines.
- Experience designing, building, or materially extending orchestration and scheduling systems, with a strong understanding of their failure modes and scaling challenges.
- Demonstrated experience with schema evolution and data correctness in systems where downstream consumers depend on reliable and stable data.
- Production experience with stateful stream-processing technologies such as Flink, Kafka Streams, Spark Structured Streaming, RisingWave, Materialize, or Feldera.
- Strong SQL and data-modelling capabilities, particularly when working with large datasets.
- Solid computer science fundamentals and a strong understanding of distributed systems.
- Experience reasoning about query execution and the underlying behaviour of data-processing engines.
- Strong debugging and root-cause-analysis skills, with a track record of driving issues through to durable production fixes.
- Strong architectural and systems-thinking abilities, with the confidence to make decisions across complex technical domains.
- Ability to take ambiguous requirements, develop a clear design and implementation sequence, and turn large technical problems into manageable workstreams.
- Strong written communication skills and the ability to collaborate effectively within distributed engineering teams.
Responsibilities
- Design and build the control plane for the curated data lifecycle, including dependency-aware orchestration, backfills, restatements, retries, partial-failure handling, and recovery mechanisms.
- Own architectural decisions across datasets, determining when a problem is best addressed through a data model, service, or job.
- Design and maintain clear contracts between data ingestion and curation layers so datasets can be understood and managed end to end.
- Build reliable alerting, monitoring, and data-quality signals that identify genuine issues while minimising operational noise.
- Work across Go, Kotlin, Rust, Python, and SQL, selecting technologies based on the requirements of each problem.
- Develop software that orchestrates and manages thousands of interdependent data models and supports large-scale data operations.
- Design systems capable of propagating schema changes and data corrections without unnecessarily disrupting downstream consumers.
- Translate ambiguous product requirements into technical designs, execution sequences, and actionable work for the broader engineering team.
- Personally implement the most technically challenging components while enabling other engineers to own and deliver complementary work.
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