About the role
VirtusLab is a leading European software consulting and engineering company. Our mission is to craft clean code and practical solutions with precision and purpose. We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering professionals to make a substantial impact in the software industry.
Requirements
Full job description: Software Engineer with Data & Quality
About the role/team
The team is responsible for developing and maintaining one of the key data processing platforms. Currently, the focus is mainly on DevOps initiatives and R&D work, which is why we're looking for someone to take ownership of the Data Quality area and have a real impact on the quality of data delivered to clients. Your main responsibility will be to identify, analyse, and eliminate data quality issues, as well as build solutions to reduce their recurrence. This is a role with a high degree of autonomy and real impact; you'll work alongside an experienced team of engineers, while also having the space to propose your own improvements and shape the overall approach to Data Quality. The project presents interesting technical challenges. Any mechanisms for improving data quality must be designed to avoid affecting production environment performance. Instead of "inline" solutions, offline approaches are used, allowing issues to be analysed and fixed without impacting data processing time. We're looking for someone who will help not only reduce the existing backlog of data quality issues, but also develop a more proactive approach to detecting and preventing problems. This is an interesting project for someone who enjoys working at the intersection of data engineering, analytics, and automation and wants to make a real impact on the stability and quality of a large data ecosystem.
Required skills:
Java - Expert
Kotlin - Advanced
Spring Boot - Advanced
Google Cloud Platform (GCP) - Advanced
BigQuery - Regular
Apache Beam - Basic
Apache Kafka - Basic
Kubernetes - Basic
Data Quality - Basic
Nice to have:
Python - Basic
Bigtable - Basic
Anomaly Detection ML - Basic
Testing Skills - Basic
Snowflake - Basic
What we expect in general:
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.
Don’t worry if you don’t meet all the requirements. What matters most is your passion and willingness to develop. Moreover, B2B need not be the only form of cooperation. Apply and find out!
Highlights
Join our team as a Data Engineer and deliver cost-effective data migrations while implementing best practices in cutting-edge data architectures!
Originally posted on Himalayas