AI Data Engineering Lead

About the Role

We’re looking for a Data Platform Engineer to build a scalable, ML-ready data foundation, unifying systems like PostgreSQL, Kafka, BigQuery, and GCS to power our AI initiatives.

Key requirements:

• Strong experience with GCP (BigQuery, Dataflow, Cloud Storage, DataStream, AlloyDB/CloudSQL).
• Advanced SQL skills.
• Experience with dbt or similar for data modeling/testing.
• Hands-on with Kafka and CDC tools (e.g., Debezium).
• Proven ability to build batch and real-time pipelines.
• Experience with dimensional modeling for analytics/ML.
• Knowledge of data governance (PII tagging, security, access control).
• Experience in data quality monitoring with automated checks/alerts.
• Familiar with data observability (freshness, schema, pipeline health).
• Skilled in BigQuery optimization (partitioning, clustering, query tuning).

Nice to Have:

• Experience with Feature Store design and ML pipelines.
• Understanding of real-time vs. batch feature serving.
• Exposure to regulated data environments.
• Familiar with Vertex AI and Apache Beam/Dataflow.
• Experience collaborating with ML/Data Science teams.
• Knowledge of vector databases or semantic search.

Benefits:

• Competitive compensation and potential for equity participation.
• Private health and dental insurance.
• High-quality equipment to support your work.
• 30 days of paid vacation.
• Flexibility to work fully remote.
• Opportunity to work abroad for up to 4 months per year.
• A high-impact role offering autonomy, ownership, and the ability to shape the data landscape.

Interview Process:

• Introductory Call
• Technical Interview
• Team Interview
• Final Interview

Apply Now by sending your CV in English with contact details in it.

Only shortlisted candidates will be invited to an interview.

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