Senior Manager Custom Analytics

GCL: E

Introduction to role:

Are you ready to lead the shift from low-code to scalable pro-code analytics that power critical decisions and ultimately better patient outcomes As the lead in Custom Analytics management you will be the hands-on engineering and change leader crafting a high-performance enterprise-grade analytics application used across our global operations.

You will champion AI-assisted development with a human-in-control ethosaccelerating delivery while safeguarding design quality security and compliance. Working closely with technical partners and multi-functional collaborators you will translate complex requirements into well-structured implementations. These will involve working with React TypeScript Python alongside FastAPI APIs quality assurance and continuous integration and delivery. Can you picture guiding teams through this transformation while leaving behind reusable patterns frameworks and guides that improve efficiency and quality across the board

We are in a period of rapid growth and digital reinvention where smarter engineering frees scientists and business colleagues to focus on discovery insight and decisions. Your work will streamline the process through which we develop analytics reduce cycle time across the SDLC and drive consistent standards-aligned delivery that scales.

Front-End Engineering: Develop reusable UI components using React TypeScript Ant Design to create a consistent maintainable user experience that accelerates feature delivery.

Backend Services: Build and maintain backend services using FastAPI (Python) to deliver reliable secure and scalable business capabilities.

API Build and Integration: Implement RESTful APIs following defined standards and guidelines enabling interoperability and performance across services.

Data Engineering: Handle data transformation aggregation and integration tasks to ensure accurate timely insights for analytics use cases.

Engineering Standards: Follow established system architecture and coding standards to ensure maintainability compliance and consistency with organizational frameworks.

Quality and Validation: Ensure code quality through testing validation and alignment with standards growing confidence in releases and reducing defects.

Performance and Debugging: Support performance optimization and debugging across the application to improve user experience and system resilience.

DevOps and Delivery: Collaborate using Docker and continuous integration and delivery pipelines to ensure smooth deployment processes and faster reliable releases.

Risk and Issue Management: Advance and communicate technical risks or blockers effectively to reduce delivery friction and protect timelines.

AI-Assisted Delivery: Use approved AI coding assistants such as GitHub Copilot Claude Code or equivalent tools to accelerate coding refactoring documentation testing debugging and solution analysis while maintaining human oversight.

Coaching and Capability Building: Coach low-code/no-code developers into pro-code practices through upskilling paired development reusable templates coding standards and guided AI-assisted workflows.

Responsible AI Guardrails: Apply guardrails for AI-generated code including human review testing security validation documentation and alignment with enterprise architecture standards.

Pro-Code Translation: Translate low-code/no-code prototypes into scalable pro-code solutions balancing rapid prototyping with maintainability extensibility performance and governance.

Patterns and Templates: Create reusable patterns repository guidance starter templates and playbooks that help AI tools produce consistent standards-aligned outputs.

Change Management: Support AI-assisted development change management through awareness enablement office hours quick-start guides feedback loops adoption tracking and reinforcement.

Cross-Functional Partnership: Partner with leads BAs solution teams and developers to reduce SDLC effort through AI across requirements design build test deployment and support.

Measurement and Reporting: Track adoption productivity quality outcomes and risks from AI-assisted practices and share progress blockers and lessons learned with stakeholders.

Strong experience with:

Python (FastAPI or similar frameworks)

REST API design and integration

Asynchronous programming

Component-based architecture

Experience with Redux Toolkit or similar state management tools

Ability to work with data structures involving aggregation and hierarchy

Clean code practices

Scalable application design

Hands-on experience or strong knowledge of AI-assisted development tools such as GitHub Copilot Claude Code ChatGPT Enterprise or approved equivalents.

Ability to use AI across the SDLC for code generation/explanation refactoring unit tests test cases debugging documentation and implementation planning.

Strong understanding of responsible AI-generated code use including review hallucination checks dependency validation privacy and security vulnerability checks.

Experience moving teams from low-code/no-code to pro-code through capability building coaching standards adoption and change management.

Ability to create developer guidance reusable prompts coding patterns repository instructions and documentation for consistent AI-assisted outputs.

Strong engineering mindset to balance rapid AI-assisted delivery with maintainability scalability quality compliance and production readiness.

Comfortable mentoring developers moving from Power Platform workflow automation or other low-code/no-code tools into React TypeScript Python APIs Git testing and CI/CD.

Experience with data visualisation tools ( Ant Design Charts)

Experience working in enterprise or large-scale environments

Experience adopting new engineering tools AI coding assistants or developer productivity platforms in team or enterprise settings.

Familiarity with ADKAR or similar change frameworks covering awareness desire knowledge ability and reinforcement.

Experience defining criteria to keep enhance or rebuild low-code/no-code prototypes as scalable pro-code solutions.

Exposure to agentic workflows AI-assisted planning coding/testing agents or repository-level AI guidance patterns.

Ability to track and communicate adoption/value metrics such as usage time saved manual steps reduced quality gains and cycle-time improvements.

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.

Join a mission-led enterprise where engineering excellence directly supports medicines that change lives and where your craft is amplified by a global collaborative network. You will work with modern stacks apply AI responsibly and shape how we build products at scalewhile partnering with diverse experts who move quickly share openly and value kindness alongside ambition. Here your decisions travel from streamlined internal operations to faster insights and better outcomes for patients with unmet needs and your curiosity is rewarded with real investment in tools learning and growth.

Own this transformation and elevate your impactsend your CV today to lead scalable analytics that matter for our teams and for patients.

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.