Director – Enterprise Data Engineering

Overview

Define and lead the enterprise standard for data engineering across AstraZeneca, building and scaling a distributed service that delivers trusted, high-quality, secure, and cost-efficient data products at enterprise scale.

What you'll do

• Define and execute the enterprise data engineering strategy aligned to the 2030 Data Strategy, translating vision into a capability model, adoption roadmap, service tiers, and maturity milestones.
• Build and lead a focused, high-performing team of specialists, setting direction on technology across acquisition, storage, ingestion, transformation, orchestration, CI/CD, and containerization using Snowflake, Fivetran, Dbt, DataOps.live, and SnowPark Container Services.
• Govern the standardization of end-to-end data engineering solutions aligned with enterprise architecture, establishing enterprise practice as a foundational pillar of data management.
• Champion automation across the lifecycle (impact analysis, design, build, test, deploy), leveraging AI code generation such as Snowflake Cortex Code and GitHub Copilot.
• Embed governance-as-code and preventative controls, design pipelines that achieve close to zero cost leakage on cloud infrastructure, and uplift latency, reliability, and quality through clear SLAs/SLOs.
• Operate and scale a federated service across business technology groups, enabling alignment, capability uplift, and reuse via onboarding kits, templates, and self-service accelerators.
• Partner with leaders across data, analytics, AI, cloud infrastructure, and enterprise, domain, and solution architecture, and liaise with procurement, finance, legal, quality, cybersecurity, privacy, and vendor partners.
• Drive adoption through education, enablement, and community practices, measuring success through standardization, automation readiness, turnaround time to business value, capability maturity, and adoption velocity.
• Proactively raise, handle, and mitigate risks, ensuring alignment to regulatory requirements including privacy, GxP, SOx, and HIPAA as applicable without slowing delivery.

What you'll need

• Preferably 15+ years in data engineering leadership roles at an enterprise capacity.
• Strong hands-on experience in data engineering capability involving data acquisition, data storage, data ingestion, data transformation, data orchestration, CI/CD, and containerization.
• Extensive practical experience engaging with open table standards (for example, Iceberg) and open technical catalogs (for example, Snowflake Horizon).
• Extensive practical experience handling structured, semi-structured and unstructured data assets and engineering.
• Mandatory skills: Snowflake, Fivetran, DBT, DataOps.live, SnowPark Container technology, Apache Iceberg, Snowflake Horizon, Snowflake Cortex software (CoCo), AWS S3.
• Expertise with modern data architectures, cloud data platforms and data engineering lifecycle implementation and practices.
• Solid understanding of metadata, lineage, security classification, FinOps, and SLA/SLO frameworks.
• Confirmed leadership in large-scale, federated, global technology environments.
• Ability to influence, educate, and lead change across technical and business teams.
• Background in regulated industries (Pharma, Healthcare) with Data Privacy, HIPAA, GxP and SOx.

Nice to have

• Track record establishing new capabilities from scratch and scaling globally.
• Experience defining enterprise service tiers, maturity models, and adoption programs.
• Proven leadership developing talent and hard-working technical teams.
• Strong collaborator management and collaboration across matrixed environments.
• A forward-thinking approach combined with a commitment to taking initiative and delivering tangible outcomes.
• Optional skills: Databricks, Snaplogic, Apache Polaris, GitHub Copilot, Claude Code, AWS Kiro, AWS Redshift, Docker, Kubernetes, MWAA, Apache Airflow, AWS Glue, Databricks Unity Catalog.

Details

• Location: Chennai, Tamil Nādu, India.
• Work mode: in-person, on average a minimum of three days per week from the office.
• Date posted 12-Nov-2026; closing date 03-Dec-2026.