Senior Director, AI-Ready Data Preparation

Posted 15 Days Ago
Be an Early Applicant
Cambridge, Cambridgeshire, England, GBR
In-Office
Senior level
Biotech • Pharmaceutical
The Role
Leads the enterprise capability for preparing, integrating, orchestrating, securing, and provisioning AI-ready data at scale. Owns reusable data products and pipelines supporting AI/ML and analytics, while implementing DataOps, automation, governance, lineage, quality controls, and compliant obfuscation. Directs engineering teams, suppliers, enterprise architecture patterns, cloud platform optimization, and self-service data capabilities. Partners with senior stakeholders to evaluate emerging technologies, demonstrate value, and scale reliable data solutions across a global organization.
Summary Generated by Built In

Senior Director, AI-Ready Data Preparation

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 outstanding connectors: you'll actively harness 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 sophisticated, 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

This role leads the enterprise capability that prepares, processes, and provisions AI-ready data at scale, using approved standards, tooling, and guidelines. The team builds and operates next generation data preparation, integration, orchestration, transfer, and obfuscation capabilities, driving increasing automation and self service for data consumers. The Senior Director also delivers and owns priority enterprise data products, demonstrating how to apply enterprise patterns end to end to accelerate time to insight for AI/ML and analytics through compliant, reliable, and efficient pipelines. Ready to develop how AI-ready data is composed and consumed across a global organisation?

Accountabilities

Lead the strategy and execution for AI-ready data preparation across high priority AI use cases, shifting from custom solutions to reusable, self-serviceable data products with growing automation. Build, own, and operate high value enterprise data products for AI/ML and analytics, applying enterprise schemas, lineage models, SLAs/SLOs, data contracts, and quality rules that drive trust and adoption. Implement DataOps practices and AI-driven automation that streamline ingestion, transformation, testing, and deployment, while enabling self-serve discovery, access, and provisioning on approved enterprise platforms. Design and run robust end-to-end data pipelines (ingest/store → prepare → provision) with scalable orchestration, metadata-driven processing, performance tuning, and cost optimisation on sanctioned cloud platforms. Apply enterprise security controls and approved obfuscation patterns such as masking, tokenisation, and anonymisation to enable safe AI experimentation and compliant data transfer at scale. Build and maintain exemplar implementations and reusable components that showcase approved ways of working for data storage, preparation, provisioning, integration, orchestration, transfer, and obfuscation. Lead and grow high performing engineering teams across onshore and offshore locations, manage suppliers effectively, and ensure on time, high quality delivery using enterprise tooling and delivery frameworks. Evaluate and pilot emerging capabilities within enterprise guardrails, make clear buy versus configure recommendations, and generate evidence of value and adoption to scale successful patterns. How will you push the boundaries of what AI-ready data can do here?

Essential Skills/Experience

•    Extensive data engineering leadership with a track record delivering production grade data products and platforms supporting AI/ML and analytics.
•    Data product and DataOps expertise: Hands on proficiency with data product contracts, lineage, quality SLAs, CI/CD for data, automated testing, and metadata driven pipelines that enable self service.
•    Integration, orchestration, and storage: Deep experience with batch/streaming integration, workflow orchestration, and scalable storage/processing on modern cloud data platforms, including performance and cost optimisation.
•    Security and obfuscation: Practical application of enterprise security controls, secure data transfer, and approved obfuscation techniques in regulated environments.
•    Architecture and design patterns: Strong command of applying enterprise data/application design patterns and microservices/event driven approaches using sanctioned tools and reference implementations.
•    Able to move at pace and lead and inspire technical team, whilst working within a rapid evolving, often ambiguous business context.
•    Innovates, experiments and brings external perspectives, with a track record of applying innovative technologies and approaches to increase speed, quality and compliance if data.
•    Partner and vendor management: Ability to influence senior collaborators, manage partner ecosystems, and build high performing teams; clear communication of value, outcomes, and adoption metrics.

Desirable Skills/Experience

Experience leading large-scale AI/ML or analytics transformation programmes in sophisticated global organisations. Background in building or operating shared enterprise data platforms or internal data marketplaces. Familiarity with regulated industries such as life sciences, healthcare, or financial services. Proven track record to translate strategic business priorities into actionable roadmaps for AI-ready data capabilities. Track record of nurturing engineering excellence through coaching, standards, and communities of practice.

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 unique and ambitious world!

AstraZeneca offers an environment where innovation in digital, data and AI directly connects to transforming patient outcomes worldwide. Curiosity is encouraged, diverse perspectives are welcomed, and teams collaborate across subject areas to solve sophisticated scientific and technical challenges with real urgency. With strong investment in technology, learning and development, alongside a culture that values experimentation and smart risk-taking, this is a place to shape the future of healthcare while building a long-term career with impact.

If this role matches your experience and ambition, apply now to help redefine how AI-ready data powers the next wave of life-changing medicines.

#EAI

Date Posted

11-Sept-2026

Closing Date

01-Oct-2026Our 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.

Skills Required

  • Extensive data engineering leadership experience delivering production-grade data products and platforms for AI/ML and analytics
  • Hands-on proficiency with data product contracts, lineage, quality SLAs, CI/CD for data, automated testing, and metadata-driven pipelines
  • Deep experience with batch and streaming integration, workflow orchestration, scalable cloud storage and processing, performance optimization, and cost optimization
  • Practical experience applying enterprise security controls, secure data transfer, and data obfuscation techniques in regulated environments
  • Strong command of enterprise data and application design patterns, microservices, and event-driven approaches
  • Ability to lead and inspire technical teams in rapidly evolving and ambiguous business contexts
  • Track record of applying innovative technologies and approaches to improve data speed, quality, and compliance
  • Ability to influence senior stakeholders, manage partners and vendors, build high-performing teams, and communicate value and adoption metrics
  • Experience leading large-scale AI/ML or analytics transformation programs in sophisticated global organizations
  • Experience building or operating shared enterprise data platforms or internal data marketplaces
  • Familiarity with regulated industries such as life sciences, healthcare, or financial services
  • Ability to translate strategic business priorities into actionable roadmaps for AI-ready data capabilities
  • Experience nurturing engineering excellence through coaching, standards, and communities of practice

AstraZeneca Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AstraZeneca and has not been reviewed or approved by AstraZeneca.

  • Fair & Transparent Compensation — Pay is considered competitive across many roles when total rewards are factored in. Senior scientific and leadership bands are described with high ranges that reinforce competitiveness at upper levels.
  • Strong & Reliable Incentives — Bonuses, equity eligibility in many salaried roles, and solid sales on‑target earnings with upside are emphasized as meaningful parts of compensation. These elements boost overall value even where base pay is not the very highest.
  • Retirement Support — A 401(k) program with a strong company match and immediate vesting is repeatedly cited as a standout. Generous retirement support is viewed as enhancing the total package relative to peers.

AstraZeneca Insights

Am I A Good Fit?
beta
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company
HQ: Gaithersburg, MD
70,000 Employees
Year Founded: 1999

What We Do

We're transforming the future of healthcare by unlocking the power of what science can do for people, society and the planet.

Similar Jobs

Samsara Logo Samsara

Account Executive

Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Easy Apply
Remote or Hybrid
London, Greater London, England, GBR
4000 Employees
10K-150K Annually

Pfizer Logo Pfizer

Clinical Development Medical Director (MD required)

Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
In-Office
3 Locations
121990 Employees
240K-400K Annually

UL Solutions Logo UL Solutions

Associate People Operations Partner

Automotive • Professional Services • Software • Consulting • Energy • Chemical • Renewable Energy
Hybrid
Basingstoke, Hampshire, England, GBR
15000 Employees

Mondelēz International Logo Mondelēz International

My Benefits Advisor UK (fixed-term contract)

Big Data • Food • Hardware • Machine Learning • Retail • Automation • Manufacturing
Hybrid
2 Locations
90000 Employees

Similar Companies Hiring

SOPHiA GENETICS Thumbnail
Software • Healthtech • Biotech • Big Data • Artificial Intelligence
Boston, MA
450 Employees
Pfizer Thumbnail
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
New York, NY
121990 Employees
Cencora Thumbnail
Healthtech • Logistics • Pharmaceutical
Conshohocken, PA
51000 Employees

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account