Associate Director, Data Engineering Services

**This is what you will do**:
Associate Director, Data Engineering Services, reports to the Head of IT Data, Insights & Analytics (DI&A) and is a critical role in Alexion IT RDU organization. The focus of this role is to take a data product-driven approach to deliver large Data & AI Programs in RDU.

Alexion is looking for a sharp-minded, assertive, and energetic DI&A leader who will be responsible for establishing the strategy, functional plans, and delivery of programs to meet the short
- and long-term goals and metrics of the organization. Should be able to engineer data solutions to meet specific business demands, enabling value from information and aligning with the overall DI&A team to ensure end-to-end delivery.

**You will be responsible for**:

- Gathering and understanding requirements via interactions with cross-functional business users, aligning on technical design with Information Architects, and converting them into technical solutions
- Work with delivery teams to test and quality assess new DI&A solutions, to ensure they are fit for release: Code Assurance, Unit and System Integration Testing, Data testing, Release Management, and support of UAT processes
- Evangelize adoption of Agile best practices, standard DevOps toolsets, and ensuring we have modern, controlled and regulated agile software development practices and a great engineering culture
- Promote and embed CI/CD to improve the software development process and transform the IT system estate into an ecosystem that delivers great user experiences and excellent IT service to the business
- Manage the 3rd Party delivery teams to drive Data Engineering operational excellence with regular performance metrics, health, scorecards and analysis reports
- Work with the Data Management team to align platform and delivery capabilities towards the development of FAIR Data Products to support AI/ML solutions
- Provide consultancy advice, as a trusted partner, to both the global and regional stakeholders within the business and other technology teams - including AZ Enterprise Architecture - from strategic partners / vendors for on-going and new implementation projects and ensure they are aligned with organization goals

**You will need to have**:

- BS with 7 plus years of industry experience leading, designing, and developing data lake and data integration architectures, using FAIR data sets and prior experience in managing end-to-end engagements in BI using Qlik Sense and Data Science languages like R and Python
- Excellent SQL, Python, Jave programming skills with hands on experience with an orchestration capability (e.g Airflow)
- Familiarity with semantic web technologies, ontology modeling, and graph algorithms
- A desire to stay up to date with cutting edge technologies in the field and streaming data processing and help further a culture of innovation and excellence within the team
- Excellent Data Modelling skills (RDBMS concepts, Normalization, dimensional modelling, star/snowflake schema etc.)
- Experience working with Git, JIRA, ServiceNow and Automated Testing tools (Jenkins, Bamboo, JIRA, Confluence, CI CD (Continuous Integration /Continuous Deployment) tools
- Knowledge of Privacy and healthcare interoperability standards like GDPR, HIPAA and HL7, FHIR
- Familiarity with Git, Data-Ops, and Continuous Integration /Continuous Deployment pipelines and experience in Agile project execution
- Experience leading a globally distributed team of Data Engineers through all phases of the development life cycles, including concept definition, product design, development, implementation, and testing
- Must be analytic, creative, and self-motivated and bring a problem-solving capability focused on continuous improvement
- Excellent communication & documentation skills, eager to learn and develop new tech skills as required

**We would prefer for you to have**:

- M.Sc. in a relevant field (such as mathematics, computer science, engineering) with 5+ years of industry experience
- Understanding and prior experience developing and maintaining physical data models, schemas, and ontologies for knowledge graphs, ensuring they accurately represent complex concepts and relationships, and optimized for performance
- Experience with graph database systems (Neo4j, Amazon Neptune, Virtuoso) and related query languages (Cypher, SPARQL)
- Prior experience with Natural Language Processing (NLP) and common machine learning models
- Domain knowledge (processes & data): Pharma Compliance, Regulatory Reporting etc.
- Prior experience working on digital health initiatives