Senior Software Engineer with Data Quality
Summary
This role involves high-performance data processing and improving data quality within a cloud-based environment using Kotlin, Java, and Spring Boot. The engineer will work with BigQuery to identify and fix data issues at scale while building remediation tooling and monitoring systems.
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.