Job Description
Job Title: Director, Enterprise Data Observability Capability Lead
GCL: F
The Director, Enterprise Data Observability Capability Lead will define and drive the strategic observability vision and execution for AstraZeneca’s Data & Analytics Platform Services (DAPS), enabling the enterprise to deliver trusted, high-quality, reliable, secure, and cost-efficient data products at scale in alignment with our 2030 Data Strategy.
This role owns the design and scaling of our federated Data Observability service, ensuring end-to-end visibility, lineage, automated quality controls, FinOps governance, performance SLAs/SLOs, and regulatory compliance across all BTGs and critical data domains. The leader will manage technology platform direction (Acceldata, DataOps.live capability), partner with metadata/governance platforms (Aperture, Collibra, BigID), and provide integrated observability insights across platforms including telemetry.
Key Accountabilities
Own and complete the enterprise Data Observability strategy aligned to AstraZeneca’s 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 monitoring and insight 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 technology divisions supporting business functions.
Lead platform vision, product roadmap, and service improvements for Data Observability:
Acceldata (DQ, lineage, FinOps monitoring, pipeline health)
DataOps.live 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, solve mentorship, and adoption of observability controls and guidelines. Drive automation-first compose, 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.
Essential Skills:
Preferably 15+ years in data observability, data platform engineering, data governance, or data quality leadership roles.
Expertise with modern data architectures and cloud data platforms.
Hands-on experience deploying or managing data observability tooling (Acceldata, Monte Carlo, Soda, BigEye, Select.dev or similar).
Experience with DataOps/DevOps practices, CI/CD testing, pipeline automation, and data lifecycle management.
Good understanding of metadata, lineage, security classification, FinOps, and SLA/SLO frameworks.
Proven leadership in large-scale, federated, global technology environments.
Ability to influence, educate, and lead change across technical & business teams.
Preferred Skills:
Experience with
DataOps.live
(SOLE/MATE/test automation).
Experience with
Snowflake
as data cloud platform.
Experience preferabily with
Acceldata
,
Select.dev
.
Familiarity with
Experian Aperture
,
Collibra, BigID
, or similar data governance tools.
Exposure to Snowflake cost governance and cloud FinOps models.
Understanding of streaming and ML observability concepts.
Background in regulated industries (pharma, healthcare) with Data Privacy, HIPAA, GxP & SOX.
Meaningful Measures & Indicators of Success:
% enterprise lineage & metadata coverage.
% automated governance controls & DQ checks.
Errors & data incidents prevented.
Team SLA/SLO compliance & performance uplift (latency, reliability, quality).
Enterprise FinOps improvements & cost avoidance.
Time-to-detect/time-to-resolve reduction.
Capability maturity & adoption velocity of business technology divisions.
Strategic problem solver with strong execution capability
Ability to build new capabilities from scratch and scale them globally
Strong collaborator across matrixed teams
Demonstrated leadership developing talent and hard-working technical teams
Collaborative, influential, and dedicated to creative solutions
Why Join Us:
This role is central to unlocking our enterprise data vision and powering trusted, efficient, and scalable AI and analytics capabilities. You will lead one of the foundational pillars of our data platform evolution, shaping how we build, govern, and trust data across AstraZeneca.
Date Posted
27-May-2026
Closing Date
18-Jun-2026
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.
