Director, Enterprise Data Observability Lead

Director Enterprise Data Observability Lead

GCL: F

Introduction to role:

Are you ready to turn data observability into a strategic advantage that accelerates life-changing medicines to patients Step in to own the enterprise capability that ensures our data is trustworthy cost-aware and this role you will shape how the company detects prevents and responds to issues across every layer of the data lifecycle directly impacting decision-making across science manufacturing and the business.

You will own the vision and execution for data observability aligned to our 2030 Data Strategy partnering across product platform security and governance teams to make reliability the default. Using platforms like Acceldata Collibra and BigID you will craft the standards automation and service model that enables global teams to adapt quickly with confidence. What could you build when lineage data quality and cost visibility are designed in from the start

Accountabilities:

Own and implement the enterprise Data Observability strategy that aligns with the 2030 Data Strategy. Create a clear adoption roadmap. Progress capability to deliver measurable reliability speed and cost outcomes.

Capability Building: Establish observability as a foundational pillar of our data platforms and governance; build and lead an enterprise team of up to 10 specialists developing best-practice frameworks across lineage automated data quality metadata FinOps SLA/SLO governance and data reliability.

Platform Product Leadership: Define platform vision and product roadmap for Acceldata observability capabilities and integrations with metadata and classification platforms; prioritize service enhancements that increase prevention automation and self-service.

Standards and Controls: Define enterprise standards SLAs/SLOs issue procedures and automated quality gates; embed governance-as-code and preventative controls into pipelines across ingestion transformation modeling and consumption.

Federated Service Model: Operate a scalable federated model that aligns business technology groups enables capabilities and ensures consistent outcomes across domains.

Telemetry and benchmarks: Set and supervise key telemetry indicators for platform health pipeline performance and data product reliability; use insights to drive continuous improvement and cost optimization.

Operational Excellence: Provide ongoing support to business technology groups for stable BAU operations including onboarding fix guidance and adoption of observability controls and guidelines.

Policy and Compliance: Establish proactive policies across data quality lineage cost performance security and GxP compliance; ensure controls are audit-ready and sustainable.

Partnership and Influence: Partner with security data governance architecture infrastructure and procurement/legal to unify standards negotiate value and remove friction; educate and enable communities of practice to drive adoption and outcomes.

Essential Skills/Experience:

• Own and implement the enterprise Data Observability strategy aligned to AstraZenecas 2030 Data Strategy.
• Define the long-term capability model enterprise adoption roadmap service tiers and maturity evolution.
• Establish observability as a foundational pillar of data platforms and data governance.
• Build and lead the enterprise Data Observability capability team (up to 10 specialists).
• Develop best-practice frameworks for lineage DQ automation metadata FinOps SLA/SLO governance and data reliability. As per Data observability capability and its sub-capabilities such as Data Quality Management Data Pipeline Monitoring FinOps and Track trace & audit.
• Operate a federated service model ensuring alignment capability enablement and scalability across business technology groups.
• Lead platform vision product roadmap and service improvements for Data Observability:
• Acceldata (DQ lineage FinOps monitoring pipeline health)
• observability capabilities (tests SOLE/MATE integration CI/CD controls)
• Integration with metadata & classification platforms (Collibra BigID)
• Telemetry monitoring and other platform key point indicators.
• Provide ongoing support to Business Technology Groups to ensure stable BAU operations including onboarding assistance fix guidance and adoption of observability controls and guidelines. Drive automation-first design governance-as-code and preventative controls embedded in pipelines.
• Define enterprise observability standards implementation SLAs/SLOs issue procedures and automated quality gates.
• Establish proactive policies across data quality lineage cost performance security & GxP compliance.
• Partner with DAPS team Cyber Security Data Governance Architecture teams Infrastructure and Procurement/Legal teams.
• Deliver reusable templates/frameworks onboarding kits and self-service accelerators.
• Drive adoption across BTGs and data domains through education enablement and community practices.
• Ensure observability is embedded across ingestion transformation modeling and consumption layers.

Desirable Skills/Experience:

• Track record leading enterprise-scale data reliability or observability programs in complex regulated environments.
• Experience maturing central capabilities in a federated operating model and influencing at executive level.
• Hands-on familiarity with Acceldata Collibra BigID and CI/CD controls for data platforms.
• Background in data platform engineering analytics engineering or data SRE with a focus on automation-first design and governance-as-code.
• Strong stakeholder management across security governance architecture infrastructure and commercial/legal functions; ability to convert standards into adoption and measurable outcomes.

When we put unexpected teams in the same room we unleash bold thinking with the power to inspire life-changing -person working gives us the platform we need to connect work at pace and challenge perceptions. Thats why we work on average a minimum of three days per week from the office. But that doesnt mean were not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Why AstraZeneca:

Here you will lead with purpose and pace bringing diverse specialists together to simplify how data flows is trusted and is used across the enterprise. We connect emerging technology with real business needs shaping decisions that matter to patients and colleagues alike. You will have room to explore advanced tooling experiment and deliver tangible improvements in reliability and speed supported by peers who value curiosity clear thinking and kindness as much as ambition. Your work will lay foundations for analytics machine learning and AI at scale turning bold ideas into dependable everyday capability.

If you are ready to build an enterprise observability capability that accelerates decisions and safeguards data at global scale step forward and shape what reliable data can achieve!

Date Posted

Closing Date

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.