ABOUT ASTRAZENECA

AstraZeneca is a global, innovation-driven BioPharmaceutical business that focuses on the discovery, development and commercialisation of prescription medicines for some of the world’s most serious disease. But we’re more than one of the world’s leading pharmaceutical companies.

At AstraZeneca we’re dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There’s no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration. Always committed to lifelong learning, growth and development.

ABOUT THE OPERATIONS IT TEAM

Operations IT is a global IT capability supporting the Global Operations organisation. We business partner with Operations capability areas: Pharmaceutical Technology Development, Manufacturing & Global Engineering, Quality Control, Sustainability, Supply Chain, Logistics and Global External Sourcing and Procurement. We operate out of Operations hub sites including in the UK, Sweden, US, and China; and out of our Global Technology Centres in India and Mexico.

Here our work has a direct impact on patients – transforming our ability to develop life-changing medicines. We empower the business to perform at its peak and lead a new way of working, combining cutting-edge science with leading digital technology platforms and data. All with a passion to impact lives through data, analytics, AI, machine learning and more.

It’s a dynamic and challenging environment to work in – but that’s why we like it. There are countless opportunities to learn and grow, whether that’s exploring new technologies in hackathons, or transforming the roles and work of colleagues, forever. This is your chance to be part of a team that has the backing to innovate, disrupt an industry and change lives.

THIS IS WHAT YOU’LL DO

We are looking for an Associate Director DataOps and Observability Lead to join our Data, Analytics & AI group for Operations IT. This group supports various business areas such as Develop, Manufacture, Supply Chain, Quality and Procurement with data-driven solutions and insights.

As the DataOps and Observability Lead, you will be responsible for leading the DataOps Team in expanding on our data product foundation. You will define the strategy, create the frameworks and standards, implement the automation managing the change management and ensure the continuous improvement of data-related workflows.

You will collaborate with stakeholders across AstraZeneca to improve the efficiency and visibility of data engineering processes and data products. You will enable our business and science teams to use data effectively ensuring the accuracy, completeness, consistency and reliability of data. You will lead a high-performing team to provide state-of-the-art DataOps and Data Observability services interacting with technologies such as Snowflake, Fivetran, dbt, Collibra and Data Quality tooling. This position requires both strategic vision and technical expertise to drive innovation in Data Engineering, Data Product Excellence and Data Management.

Typical accountabilities include:

Leadership

• Provide strategic leadership to a team of talented dataops engineers, fostering a culture of collaboration and innovation, and enabling people to be at their best.

• Guide the development, execution and implementation of a roadmap for DataOps & Data Observability services, aligned with organizational objectives.

• Accountable for overseeing change management activities which drive process efficiencies through DataOps platform enhancements.

DataOps Platform

• Oversee the design, implementation, and optimization of robust DataOps services and platforms to ensure efficient data processing, transformation, and storage across the organization.

• Collaborate with cross-functional teams understanding, learning, and applying new automated build, test and deployment capabilities focused on data products and help develop project teams towards integrating such solutions.

• Collaborate with the data engineering team to optimize data workflows and ensure efficient data operations, regularly checking for continuous improvement and driving efficiencies & automation in data engineering.

• Collaborate with solutions architecture to ensure platforms design and infrastructure is scalable, secure and cost effective.

• Identify opportunities for innovation and promote initiatives to enhance the data platform's capabilities and efficiency.

• Create and maintain comprehensive documentation, including dataops processes, standard operating procedures, and best practices.

• Design, implement, and sustain a DataOps framework, facilitate cross-team collaboration, optimize processes & tools, leverage testing automation.

• Implement the CI/ CD Automation & DataOps in each of the Data Products in Optimum Delivery by producing a phased roadmap along with the Tools fitment.

• Create and maintain comprehensive active metadata management strategy to enable and accelerate DataOps, understanding how we use our data catalogue effectively.

Data Observability Platform

• Develop, communicate, and implement a cross departmental data quality & observability strategy, with a focus on data product delivery initially aligned with organizational objectives.

• Establish and enforce data quality standards, guidelines, and best practices across the organization. Collaborate with data owners and stakeholders to define data quality requirements.

• Continuously review and enhance data quality processes and tools to adapt to changing business needs and improve overall data quality practices.

• Ensure Data Quality rules are defined and captured within our data catalogue tool.

Technology Stack Management

• Stay abreast of emerging technologies and industry trends to continuously enhance the organization's DataOps & Data Observability capabilities.

• Manage and optimize the technology stack, ensuring alignment with security, architecture, compliance, and performance standards.

• Integration with data catalogue.

Team Development

• Recruit, mentor, and develop a high-performing team of dataops & data observability engineers, fostering a culture of continuous learning and growth.

• Provide guidance on technical challenges and ensure professional development opportunities for team members.

Stakeholder Collaboration

• Collaborate with stakeholders across departments to understand data requirements and ensure that DataOps services meet business needs.

• Act as a liaison between IT and Business Units, fostering strong communication and understanding.

• Oversight of partnerships with multiple third parties, academic or outsourced partners to shape and drive project outcomes and knowledge building.

Quality Assurance

• Implement and oversee robust quality assurance processes to ensure the accuracy, reliability, and security of data.

• Establish and monitor key performance indicators to measure the effectiveness of DataOps & Data Observability services.

YOU WILL NEED TO HAVE

• A passion for technology and continuous improvement.

• Proven experience in leading and managing teams in delivering DataOps & Data Observability solutions, ideally from a global organisation with multiple partners, internal stakeholders and team members that are geographically and culturally diverse.

• A solid understanding of data quality concepts; experience of managing, controlling, reporting data quality and integrity and reporting outcomes in KPIs.

• Strong technical background in data management, Cloud computing (ideally AWS), and relevant technologies.

• Strategic thinking – understanding challenges, opportunities through evolving technology/methodology and formulating into tangible roadmaps with clear business value.

• Software languages (particularly Python, SQL)

• Leadership abilities, with a proven history of continually growing and motivating teams

• Effective communication and interpersonal skills, with the ability to collaborate effectively with technical and non-technical stakeholders.

• Knowledge of the pharmaceutical industry, particularly around data requirements and compliance standards (GXP, GDPR, SoX etc).

• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

Professional certifications in the following fields:

• Data Engineering and related technologies (eg AWS, Snowflake, dbt Cloud, Graph, Data Catalogue)

• Data Management (e.g. CDMP through DAMA)

In addition, it is desirable for candidates to have:

• High project management skills, including the ability to plan multiple priorities, meet deadlines, and deliver good outcomes.

• Proven track record of delivering Knowledge Graphs

• Working experience of Data Catalogues

• Experience in life sciences and healthcare.

WHY JOIN US

Here our work has a direct impact on patients – transforming our ability to develop life-changing medicines. We empower the business to perform at its peak and lead a new way of working, combining cutting-edge science with leading digital technology platforms and data. All with a passion to impact lives through data, analytics, AI, machine learning and more.

Join us at a crucial stage of our journey in becoming a digital and data-led enterprise. Make the impossible possible by building partnerships and ecosystems, creating new ways of working and driving scale and speed to deliver exponential growth. Focused and committed, and backed with the investment to succeed, we’re driving cross-company change to disrupt the entire industry.

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.