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Director, Data Automation

UK - Cambridge

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Employment
Full-time — employment source
Employment type in the employer’s listing: Full time
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Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
We're building a connected, end-to-end Enterprise AI engine - uniting data foundations, AI technology, process reinvention, and business-facing AI to accelerate results across the whole value chain. Success depends on being exceptional connectors: you'll actively leverage existing capabilities, celebrate and promote reuse, export breakthrough ideas across geographies and functions, and obsess over scaling impact rather than building in isolation. If you thrive in high-collaboration environments where your role is to turn complex, cross-functional problems into reusable, enterprise-wide capabilities - and where the measure of success is adoption and scale, not just innovation - you'll have the platform (and sponsorship) to make it real.
Read the full posting
Apply at AstraZeneca

What you’ll bring

All qualifications

Core experience

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, or related discipline.
  • 8+ years of experience in data engineering, data platform development, or related disciplines.
  • Experience designing and building data pipelines and ETL/ELT processes.
  • Ability to influence across cross-functional teams.
  • Experience implementing self-service data platforms and data product operating models.
  • 2+ years leading technical teams and delivering complex data initiatives.

Preferred experience

  • AWS preferred
Qualification wording
Bachelor's or Master's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, or related discipline.
8+ years of experience in data engineering, data platform development, or related disciplines.
Experience designing and building data pipelines and ETL/ELT processes.
Ability to influence across cross-functional teams.
Experience implementing self-service data platforms and data product operating models.
2+ years leading technical teams and delivering complex data initiatives.
Experience with cloud data platforms (AWS preferred).

Tools in this posting

  • Python
  • SQL
  • AWS
  • Databricks
  • Prefect
  • Snowflake
  • Spark
  • Airflow
Source — Tool mentions in context
Technical Skills - Strong hands-on experience with Python and SQL. - Experience designing and building data pipelines and ETL/ELT processes.
- Experience designing and building data pipelines and ETL/ELT processes. - Experience with cloud data platforms (AWS preferred). - Knowledge of orchestration frameworks (e.g., Airflow, Data Factory, Prefect).
- Experience with Spark or distributed data processing technologies. - Experience with Spark, Snowflake, Databricks or distributed data processing technologies. - Understanding of data modelling, metadata, lineage, and data quality frameworks.
- Experience with cloud data platforms (AWS preferred). - Knowledge of orchestration frameworks (e.g., Airflow, Data Factory, Prefect). - Experience with Spark or distributed data processing technologies.
- Knowledge of orchestration frameworks (e.g., Airflow, Data Factory, Prefect). - Experience with Spark or distributed data processing technologies. - Experience with Spark, Snowflake, Databricks or distributed data processing technologies.

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First seen by us
Oct 21, 2026 · today
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Your next step

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Job description

View original posting ↗

We're building a connected, end-to-end Enterprise AI engine - uniting data foundations, AI technology, process reinvention, and business-facing AI to accelerate results across the whole value chain. Success depends on being exceptional connectors: you'll actively leverage existing capabilities, celebrate and promote reuse, export breakthrough ideas across geographies and functions, and obsess over scaling impact rather than building in isolation. If you thrive in high-collaboration environments where your role is to turn complex, cross-functional problems into reusable, enterprise-wide capabilities - and where the measure of success is adoption and scale, not just innovation - you'll have the platform (and sponsorship) to make it real. 

Introduction to role: 

Are you ready to build intelligent automation that makes trusted data instantly available for the decisions that change patient outcomes and accelerate our business? Do you see yourself leading a high-performing team to transform how data fuels analytics, AI and digital products across a global enterprise? 

As Director, Data Automation, you will lead a team of data engineers and automation specialists to design, deliver and scale modern data products and automated workflows. Your leadership will ensure our data is reliable, reusable and secure powering everything from research insights to operational excellence. You will partner with domain experts, product leaders and technologists to embed best-in-class engineering practices, orchestration and data quality into the backbone of our digital transformation. 

Accountabilities: 

- Leadership and Team Development: Lead, mentor and grow a team of data engineers and automation engineers; establish engineering standards and ways of working; manage priorities, capacity and delivery commitments; foster a culture of automation, continuous improvement and operational excellence; support recruitment, performance management, career development and succession planning. 

- Data Engineering: Design and oversee scalable data pipelines and data products; ensure reliable ingestion, transformation, integration and delivery of structured and unstructured data; drive reusable architectures, metadata and lineage capabilities; champion CI/CD, testing, observability and Infrastructure-as-Code; ensure performance, scalability, security and compliance are built in. 

- Data Automation: Identify and automate manual data processes and operational workflows; lead adoption of workflow orchestration, automation frameworks and self-service capabilities; develop automated monitoring, alerting, reconciliation and quality controls; improve efficiency through standardization and intelligent automation; prioritize automation opportunities with measurable business impact. 

- Data Quality, Governance and Compliance: Implement controls for data accuracy, completeness, consistency and traceability; align with enterprise data standards and policies; ensure appropriate controls for regulated and sensitive data; support audit readiness and compliance; promote FAIR and data stewardship principles where applicable. 

- Stakeholder Management: Collaborate with business functions, data product owners, analytics teams and enterprise technology; translate business requirements into scalable technical solutions; communicate progress, risks, dependencies and delivery outcomes to leadership; act as a trusted advisor on data engineering and automation capabilities. 

Essential Skills/Experience: 

Education 

- Bachelor's or Master's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, or related discipline. 

Experience 

- 8+ years of experience in data engineering, data platform development, or related disciplines. 

- 2+ years leading technical teams and delivering complex data initiatives. 

- Proven experience delivering enterprise-scale data platforms and automated data solutions. 

Technical Skills 

- Strong hands-on experience with Python and SQL. 

- Experience designing and building data pipelines and ETL/ELT processes. 

- Experience with cloud data platforms (AWS preferred). 

- Knowledge of orchestration frameworks (e.g., Airflow, Data Factory, Prefect). 

- Experience with Spark or distributed data processing technologies. 

- Experience with Spark, Snowflake, Databricks or distributed data processing technologies. 

- Understanding of data modelling, metadata, lineage, and data quality frameworks. 

- Familiarity with DevOps practices, CI/CD, Git, automated testing, and monitoring. 

- Experience with both structured and unstructured data. 

Leadership Competencies 

- Strategic thinking and problem solving. 

- People leadership and coaching. 

- Strong stakeholder engagement. 

- Delivery and execution focus. 

- Continuous improvement mindset. 

- Ability to influence across cross-functional teams. 

- Strong communication and collaboration skills. 

Desirable Skills/Experience: 

- Background in regulated industries and audit-ready data controls. 

- Experience implementing self-service data platforms and data product operating models. 

- Exposure to streaming data, event-driven architectures and real-time automation. 

- Experience partnering with data science and ML engineering teams to productionize models. 

- Knowledge of privacy, security and compliance-by-design for sensitive data domains. 

Why AstraZeneca: 

Join a company where digital, data and science come together to improve patient lives at scale. You will have the backing to innovate with modern platforms, the freedom to experiment with AI and automation, and the chance to bring unexpected teams into the same room to unleash bold thinking. Here, your work sets direction early in major initiatives, accelerates how our colleagues operate every day and shapes decisions that ripple across the enterprise—all while valuing kindness alongside ambition and ensuring you have the support to grow. 

Call to Action: 

Step into a role where your leadership in data automation will create trusted, reusable data assets and unlock new possibilities for patients and the business—seize this opportunity to lead the next leap forward! 
 
#EAI 

Date Posted

21-okt.-2026

Closing Date

28-okt.-2026

Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.
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Location & working pattern

UK - Cambridge

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We're building a connected, end-to-end Enterprise AI engine - uniting data foundations, AI technology, process reinvention, and business-facing AI to accelerate results across the whole value chain. Success depends on being exceptional connectors: you'll actively leverage existing capabilities, celebrate and promote reuse, export breakthrough ideas across geographies and functions, and obsess over scaling impact rather than building in isolation. If you thrive in high-collaboration environments where your role is to turn complex, cross-functional problems into reusable, enterprise-wide capabilities - and where the measure of success is adoption and scale, not just innovation - you'll have the platform (and sponsorship) to make it real. Introduction to role:

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