Data Engineer

We’re hiring a Data Engineer with specialized experience in Feature Store design and implementation to support a critical phase in our ML platform modernization effort. This role is ideal for someone who knows their way around Feast, Tecton, or Vertex AI Feature Store internals, and can build robust, scalable data pipelines for ML feature serving.

Key Responsibilities:

• Lead the design and implementation of a centralized Feature Store to support both batch and real-time ML workloads.
• Develop scalable data pipelines for feature ingestion and transformation using tools like Apache Beam or Spark.
• Design data models tailored for ML feature serving, covering versioning, freshness, and consistency guarantees.
• Build real-time ingestion flows using stream processing frameworks like Kafka or Pub/Sub.
• Collaborate with MLOps engineers and data scientists to ensure seamless integration with model pipelines and CI/CD workflows.
• Evaluate tradeoffs of using custom Feast-based implementations vs. managed services (e.g., Vertex AI FS).

Required Skills:

• Deep experience with Feature Store technologies (Feast, Tecton, or Vertex AI Feature Store).
• Strong grasp of data modeling for machine learning and real-time vs. batch processing trade-offs.
• Solid background in big data tools like Apache Spark, Apache Beam, or similar.
• Proficient in stream processing and messaging systems (Kafka, Pub/Sub).
• Advanced SQL skills and comfort working with large-scale structured data.

Bonus Points:

• Hands-on experience building or extending Feast in production environments.
• Familiarity with GCP and how Vertex AI Feature Store integrates with broader GCP ecosystem.
• Exposure to ML feature lineage, version control, and governance practices.

We offer:

• Employment in a stable, well-recognized international company
• Competitive salary and benefits
• Tolerant and diverse environment
• A friendly team of professionals
• Flexible working hours
• Medical insurance
• Training programs and excellent travel conditions