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Director – Enterprise Data Engineering

AstraZeneca
NewPosted yesterday

LOCATION

Chennai · Hybrid

EXPERIENCE

15+ Years

TYPE

FullTime

SKILLS REQUIRED

Data EngineeringSnowflakeData GovernanceData PipelinesDBTApache IcebergRegulatory Compliance

Job description

Overview

Lead the definition and scaling of AstraZeneca's enterprise data engineering strategy and capability, delivering trusted, secure, cost-efficient data products across the organisation.

What you'll do

  • Define and execute the enterprise data engineering strategy aligned to the 2030 Data Strategy, including capability model, adoption roadmap, service tiers and maturity milestones.
  • Build and lead a focused, high-performing team of specialists and set direction on technology across acquisition, storage, ingestion, transformation, orchestration, CI/CD and containerization using Snowflake, Fivetran, Dbt, DataOps.live and SnowPark Container Services.
  • Govern standardization of end-to-end data engineering solutions aligned with enterprise architecture and establish enterprise practice as a foundational pillar of data management.
  • Champion automation across the lifecycle, leveraging AI code generation (for example, Snowflake Cortex Code and GitHub Copilot) to increase velocity and quality and reduce defects and time-to-detect/time-to-resolve.
  • Embed governance-as-code and preventative controls, design pipelines and patterns achieving 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/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 and 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) 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

  • Optional skills: Databricks, Snaplogic, Apache Polaris, GitHub Copilot, Claude Code, AWS Kiro, AWS Redshift, Docker, Kubernetes, MWAA, Apache Airflow, AWS Glue, 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, India.
  • Work mode: on average a minimum of three days per week from the office, with individual flexibility.
  • Date posted 12-Nov-2026; closing date 03-Dec-2026.

Read the full description and apply on the company’s own careers page.

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Director – Enterprise Data Engineering