Director – Enterprise Data Engineering

Overview

Define and execute AstraZeneca's enterprise data engineering strategy, building and scaling a distributed service that delivers trusted, high-quality, secure and cost-efficient data products at enterprise scale. Own the end-to-end data engineering capability, connecting strategy to execution across business technology groups.

What you'll do

• Define and execute the enterprise data engineering strategy aligned to the 2030 Data Strategy.
• Translate the vision into a capability model, adoption roadmap, service tiers and maturity milestones that build measurable business value.
• Build and lead a focused, high-performing team of specialists.
• Set direction on technology across data acquisition, storage, ingestion, transformation, orchestration, CI/CD and containerization.
• Govern standardization of end-to-end data engineering solutions aligned with enterprise architecture.
• Establish enterprise data engineering practice as a foundational pillar of data management.
• Champion automation across impact analysis, design, build, test and deploy.
• Leverage AI code generation, including Snowflake Cortex Code and GitHub Copilot, to increase velocity and quality while reducing defects and time-to-detect/time-to-resolve.
• Embed governance-as-code and preventative controls.
• Design pipelines and patterns that achieve close to zero cost leakage on cloud infrastructure.
• Uplift latency, reliability and quality through clear SLAs/SLOs.
• Operate and scale a federated service across business technology groups.
• Enable alignment, capability uplift and reuse through onboarding kits, templates and self-service accelerators.
• Partner with leaders across data, analytics, AI, cloud infrastructure and enterprise, domain and solution architecture.
• Liaise with procurement, finance, legal, quality, cybersecurity, privacy and vendor partners to ensure compliant, secure and value-driven delivery.
• Drive adoption through education, enablement and community practices.
• Measure success through standardization, automation readiness, turnaround time to business value, capability maturity and adoption velocity.
• Raise, handle and mitigate risks.
• Ensure 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.
• Extensive practical experience engaging with 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) and 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, including Pharma and Healthcare, with Data Privacy, HIPAA, GxP and SOx.

Nice to have

• Optional skills: Databricks, Snaplogic, Apache Polaris, GitHub Copilot, Claude Code, AWS Kiro, AWS Redshift, Docker, Kubernetes, MWAA, Apache Airflow, AWS Glue and Databricks Unity Catalog.
• 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.

Details

• Location: Chennai, Tamil Nādu, India.
• In-person working is expected, on average, a minimum of three days per week from the office.
• The working arrangement balances the expectation of being in the office with individual flexibility.