Data Engineer

Our client is a global leader in cybersecurity for IT, OT, and ICS critical infrastructure. Their end-to-end platform gives enterprises and public sector organizations the critical advantage they need to protect complex networks, secure devices, and meet compliance requirements.

Over the past 20 years, a consistent commitment to innovative technology has earned the trust of more than 1,700 organizations, governments, and institutions worldwide — cementing the company's role in protecting the world's critical infrastructure and securing our way of life.

As a Machine Learning Engineer you will own the data foundation the team runs on: dataset pipelines, labeling workflows, and data quality. Model quality is bottlenecked by data quality; this role removes that bottleneck.

You Will Have the Opportunity to

- Build and maintain dataset ingestion, cleaning, and versioning pipelines (training, validation, and held-out evaluation sets)

- Design and operate labeling workflows, including quality control and inter-annotator agreement tracking

- Own dataset testing: coverage analysis, class balance, leakage detection, dataset documentation

- Manage dataset versioning and lineage so every model release traces back to exact training data

- Partner with data science and product engineering teams on data-sharing boundaries and formats

Requirements

- 3+ years data engineering experience; strong Python and SQL

- Experience with data versioning tools (DVC, LakeFS, or similar) and pipeline orchestration (Airflow, Dagster, or similar)

- Understanding of ML-specific data concerns: train/test leakage, label noise, distribution shift

- Rigor in documentation and reproducibility

Benefits

- Stable, growing international company background with an exceptional customer group

- Opportunity to improve your professional skills

- The newest technology environment

- Language course and opportunity for active recreation – kettlebell, football and office massage

- Attractive working environment – nice office full of accessories (fruits every day, coffee, breakfast, tea etc.)

- Regular team events and Happy Hour activities