AstraZeneca
From AstraZeneca's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
In this role, you will establish the main direction for data engineering across AstraZeneca.
Job Title: Director – Enterprise Data Engineering
GCL: F
Are you ready to define the enterprise standard for data engineering and turn strategy into measurable outcomes that accelerate insights to patients? In this role, you will establish the main direction for data engineering across AstraZeneca. You will be responsible for building and scaling a distributed service that provides trusted, high-quality, secure, and cost-efficient data products at enterprise scale.
You will own the end-to-end build of our data engineering capability. This includes driving visibility and lineage, automated quality controls, FinOps governance, performance SLAs/SLOs, and regulatory compliance across crucial information domains. Working as part of a varied community of specialists, you will connect strategy to execution, partnering across business technology groups to standardize how data is acquired, transformed, orchestrated, and delivered for impact. Can you turn a long-term architecture into reusable accelerators that dozens of teams embrace and love?
Define and execute the enterprise data engineering strategy aligned to our 2030 Data Strategy; translate 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 perfection 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; establish enterprise practice as a foundational pillar of data management.
Champion automation across the lifecycle—impact analysis, design, build, test, deploy—leveraging AI code generation (for example, 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, and uplift performance metrics including latency, reliability, and quality through clear SLAs/SLOs.
Operate and scale a federated service across business technology groups; enable 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; 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.
Proactively raise, handle, and mitigate risks; ensure alignment to regulatory requirements (including privacy, GxP, SOx, and HIPAA as applicable) without slowing delivery.
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, containerization.
Extensive practical experience engaging with Open table standards (for ex, Iceberg) and Open technical catalogs (for ex, Snowflake Horizon).
Extensive practical experience handling Structured, Semi-Structured and Unstructured data assets and engineering.
Mandatory (Must Have) Skills – Snowflake, Fivetran DBT, DataOps.live, SnowPark Container technology, Apache Iceberg, Snowflake Horizon, Snowflake Cortex software (CoCo), AWS S3.
Optional (Nice to Have) Skills – Databricks, Snaplogic, Apache Polaris, GitHub Copilot, Claude Code, AWS Kiro, AWS Redshift, Docker, Kubernetes, MWAA, Apache Airflow, AWS Glue, Databricks Unity Catalog.
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 & business teams.
Background in regulated industries (Pharma, Healthcare) with Data Privacy, HIPAA, GxP & SOx.
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.
When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our outstanding and ambitious world.
Here you will build from scratch with a collective of inclusive self-starters who share ideas, challenge with grit, and make bold thinking real. We bring unexpected teams into the same room—engineers, scientists, analysts, and partners—using brand-new data and AI tools to turn complexity into practical insights that help patients sooner. You will work at the heart of our information transformation. u will have the autonomy to set direction and the community support to deliver it. You will balance ambition with care while scaling solutions across a worldwide information ecosystem.
Lead the enterprise backbone supporting data engineering and watch your strategy translate into faster, trusted insights for patients—step forward and build what comes next.
AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.
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