Senior Analyst - Data Analysis Specialist
JOB TITLE : SENIOR ANALYST
CAREER LEVEL: D2
Embrace novel and varied challenges working across the business
Be connected to different functions, areas and roles across the business. We are supported by leaders in our aspiration to break down boundaries and draw on inter-functional learnings. It means we get to face interesting business problems and varied data. One day working along the whole development cycle from molecules to delivery, the next supporting HR processes or medicine launches
AstraZeneca is a global, science-led, patient-focused biopharmaceutical company 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.
About the team
A team of deep specialists, our skills range from mathematics to computation. Our diversity is our strength. We turning complex information into lifechanging and practical insights, every day. Our progressive operating model means that we stay at the forefront. Evolving and learning from what we’re seeing externally.
We impact patients lives. Empowering and enabling the business to run faster and better, we play a part in improving lives across the world.
About the role
Data Analysis Specialist is responsible for supporting more complex data challenges (size, complexity, type and/or number of data sets) under the supervision of more experienced Data Analysts
The role holder will implement the following accountabilities either autonomously for simple data analysis challenges or under the supervision of more senior data analysts for more complex data challenges
For simpler analysis challenges, works with consumers / business users on the definition of the data requirements for intended data solutions. Able to translate unstructured business problems into a data design and solution
Profiling of data to understand provenance, quality, metadata models, ownership and compliance to internal and external regulatory standards
Ad hoc wrangling of data (sourcing, extraction, profiling, integration) to support Data Science model generation and business insight
Support of data engineers in the development of Source to Target pipelines (e.g. ETL design)
Design & testing of the quality and performance of derivative data models in downstream reporting and analytics solutions
Processing of requests for compliant access to data
Defining and managing information lifecycle management in data solutions
Provision of data understanding (structure, provenance, quality) to Architects, Data Engineers and Data Scientists to support use in Analytics projects.
Supports IT and business data teams in identifying and managing Critical Data Assets and Elements including Reference, Master and Metadata.
Collaborates with Risk, Assurance, Privacy, Information Security and Regulatory authorities to ensure data and information controls are in place and adhered to.
Clearly and objectively communicate insights and results, as well as their associated uncertainties and limitations
Personal development and training in more complex data analysis skills, techniques and tooling
Will be developing domain data expertise (data standards, systems, metadata models, policies, business processes) in 1 area (e.g. chemistry, finance)
3 key specialisms include:
Source Data Analysts: Support engineers build/configure source applications by defining the data requirements and modeling the appropriate data structures for given use cases. They define data quality criteria to ensure data quality integrity of the application, develop logical data models (compliant to any RMDM standards), ensure that the project deliverable aligns with the logical design and business requirements (requirements traceability).
Integration Data Analyst: Support engineers build composite analytics applications by defining data requirements, data structures and data integration paths. They will identify, profile and quality assess potential source data sets, understand and align with any data restrictions (e.g. GDPR, License, IDAP controls, etc), develop integration patterns (ETL design), support the design of target data models (compliant to any MDM standards) and document to support re-use and management of the application.
Data Steward: defining and managing data governance policies, standard and operating processes; the facilitation and operation of data and information governance activities; data quality issue management; the establishment and operation of governance controls including data access, lifecycle and metadata management; risk based approach to remediation and mitigation planning.
Education, Qualifications, and Experience
Undergraduate degree in a Computer Science, Data Management or possibly discipline area (R&D, Finance, HR etc) and cross trained or equivalent number of years of experience
Demonstrated experience in a data analyst or business role aligned to data and information management role with practical examples of performing data analysis in terms of defining requirements, gleaning critical data elements, defining data quality criteria and checkpoints
Post-graduate degree in MIS, Data Management
Domain data understanding: the structure, provenance and meaning of the source data crucial to the domain (eg. SAP for Finance, SDTM for Clinical). Understanding of the business processes in the generation and consumption of data
Skills and Capabilities
The role holder will possess a blend of data requirement analysis, data quality analysis, data stewardship skills
Experience in translating requirements into fit for purpose data models, data processing designs and data profile reportsExperience in the use of data modeling technologies
Experience in Agile data definition scrumsExperience in the use of metadata cataloguing tools
Knowledge of key AZ policies and standards for data covering areas such as privacy and security.
Good written and verbal communication and consultancy skills
Awareness of the end to end processes and activities in the build and support of Data solutions
Experienced in applying a risk based methodology to data and information management
Experience of Data Analysis enabling tool kits
Experience in working in multi-skilled, multi-location data teams, working to agile principles.
Experience in life sciences and healthcare
Experience in a complex global organization
WHY JOIN US ?
A place to do important work. We connect across the whole business to power each function to better influence patient outcomes and improve their lives. Impactful and valuable, this is where you come to raise your profile and do good for others. Rise to the challenge of shaping the future of an evolving business in the technology space.
SO, WHAT’S NEXT?
Are you already envisioning yourself joining our team? Good, because we’d love to hear from you! Click the link to apply and we’ll be in touch as soon as we can.
WHERE CAN I FIND OUT MORE?
Our Social Media, Follow AstraZeneca on LinkedIn https://www.linkedin.com/company/1603/
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.
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 authorisation and employment eligibility verification requirements.