We’re looking for a Senior or Lead Data Engineer to join our core technical team and architect the systems that make everything else possible - from real-time data flows to ML model training, product analytics, and beyond.

You’ll be the backbone of our data infrastructure - someone who sees pipelines not as a feature, but as a living system that unlocks every other part of the company.

What You’ll Be Doing

• Design, build, and own data pipelines (batch + streaming) across the business

• Architect scalable, reliable data lake / warehouse environments (e.g. BigQuery, Snowflake, Redshift)

• Partner with ML engineers, product teams, and analysts to build clean, fast, well-documented datasets

• Drive adoption of best practices in data versioning, observability, governance, and reproducibility

• Support downstream teams with feature engineering, evaluation data sets, and analytics layers

• Lay the foundation for modern experimentation, personalisation, and feedback loops

What We’re Looking For

• 5+ years of experience in data engineering / infrastructure roles

• Strong Python or Scala skills, with modern data tooling (Airflow, Spark, dbt, etc.)

• Cloud-native mindset: experience with GCP, AWS, or Azure, and distributed data systems

• Deep knowledge of SQL and data modeling for scale

• Experience working with ML teams or data for AI/analytics

• Leadership traits: able to drive projects, mentor others, own systems end-to-end

🌱 Nice-to-Haves

• Experience with audio, time-series or unstructured data

• Exposure to ML feature stores, embeddings, or vector DBs

• Interest in generative AI, creativity tools, or developer platforms

• Familiarity with privacy / compliance-aware data architectures (GDPR, HIPAA, etc.)