Senior Software Engineer with Data Quality
Tech stack:
- Kotlin
- Java
- Spring Boot
- Google Cloud Platform (GCP)
- BigQuery
- Bigtable
- Snowflake
- Apache Beam
Challenges
- challenges related to high-performance data processing and large system scale,
- working with a modern technology stack in a cloud environment.
- AI Native Organisation
Team
Around the product, there are a couple of subteams; you will be the third teammate of the Data Quality team that focuses on improving the quality of the data portfolio.
A few perks of being with us
- Building tech community
- Flexible hybrid work model
- Home office reimbursement
- Language lessons
- MyBenefit points
- Private healthcare
- Training Package
- Virtusity / in-house training
- And a lot more!
– Data analyst instincts + software engineer’s hands. ~70% of the job is finding a cohort in BigQuery, working out why the data is wrong, and fixing it at scale. Strong SQL and genuine curiosity about data are non-negotiable.
– JVM backend (Kotlin/Java, Spring Boot). Must be able to build their own remediation tooling and checks, not just run queries. Beam/Dataflow, Kafka, Snowflake, Bigtable are a plus, not a must.
– Data quality/observability mindset. Has built monitors, data tests, or anomaly detection. Understands the difference between firefighting and building prevention and wants the second.
– Ownership and autonomy. The backlog is unassigned and partly undefined. They must take a vague ticket, scope it themselves, deliver, and propose what’s next. Fluent English, direct work with the US team, remote.
– Comfortable with legacy and ambiguity. A live, latency-sensitive system where fixes run offline, and validation is statistical, not a green test. No greenfield here.