Director – Enterprise Data Engineering
AstraZeneca (company site, opens in a new tab)15+ yrsChennaiOn-siteDirect career pageEst. 40–70 LPA
Posted 11h ago
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Job description
Structured overview of role & requirements
About This Role
- Set enterprise data engineering strategy and turn it into a capability model, adoption roadmap, service tiers, and maturity milestones.
- Build and scale a federated service and specialist team delivering reusable, trusted, secure, cost-efficient data products across business technology groups.
- Own standards and outcomes for automation, lineage, data quality, FinOps, performance SLAs/SLOs, and regulatory controls across the data engineering lifecycle.
Minimum Requirements
- Work Experience Required: Preferably 15+ years in data engineering leadership at enterprise scale; this is stated as a preference, not a strict minimum.
- Mandatory skills: Snowflake, Fivetran, dbt, DataOps.live, Snowpark Container technology, Apache Iceberg, Snowflake Horizon, Snowflake Cortex software (CoCo), and AWS S3.
- Practical data engineering experience across acquisition, storage, ingestion, transformation, orchestration, CI/CD, and containerization; experience with structured, semi-structured, and unstructured data and open table/catalog standards.
- In-person work averages at least three days per week; location is Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Has led enterprise-scale, federated data engineering across global technology environments, aligning business and technical groups around shared standards and adoption.
- Can establish a data engineering capability from scratch and scale it using service tiers, maturity milestones, reusable accelerators, automation, and measurable operational outcomes.
- Brings regulated-industry experience—particularly pharma or healthcare—and can embed privacy, GxP, SOx, HIPAA, security, and governance controls into delivery.