Job Description
Own end-to-end engineering delivery for data pipelines, curated datasets, and ML engineering outcomes (feature/serving pipelines and model integration), ensuring strong engineering practices (version control, testing, CI/CD), data quality, observability, and operational readiness.
Description
- Lead and grow the Data Engineering & ML Engineering team (hiring, onboarding, performance management, coaching, career development).
- Act as a hands‑on technical lead (player/coach): drive technical direction, review designs and code, unblock complex engineering problems, and set reusable patterns and standards.
- Own end-to-end engineering delivery for data pipelines and curated datasets (data products) on Azure Databricks, ensuring quality, reliability, security and operational readiness.
- Lead ML engineering delivery in partnership with Data Science and MLOps (feature engineering pipelines, training/inference integration, model packaging a...
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