Data Engineer - Microsoft Azure stack
£600 - £700 via Umbrella
GlaxoSmithKline - Brentford
3 months initially
This is a hands-on role that works closely with the internal and externally-sourced analytical communities to streamline and simplify access to internal and external data (public and licensed), critically requiring both interpersonal skills and technical/data handling skills.
This role will contribute to the establishment of an internal knowledge base of integrated data sets, artefacts, and key business and IT contacts to enable more streamlined and efficient future business and IT endeavours.
This role will follow GSK data handling policies and standard processes and propose changes to policies and processes that are too restrictive and limit our ability to operate at the speed of the business.
This role will network externally to leverage industry best practices and share best practices as appropriate.
This role will work collaboratively with Information Architects and Information Management Services to leverage and support proactive data management.
This role will contribute to a strategic plan to develop and mature this service over a multi-year period, identifying and prioritizing key opportunities for simplification and acceleration of value associated with this service.
· Work closely with the Director of Data Engineering, Engineering Leads to define and implement a Data Engineering Strategy that enables business transformation by streamlining access to data assets.
· Take a highly proactive approach to understanding, shaping, and leveraging existing CH data sources – internal and external
· Build a network of relationships across the GSK Business and IT in identifying the right contacts for the facilitation of data access and integration.
· Work with projects, use case leads and other Business/IT customers to responsibly and securely enable data access to internal and the growing external data sources into a form that can readily be used by analytical methods to support business transformation;
· Through close collaboration with the other teams like data team, data science team, digital and more, recognize and build novel and strategic relationships between diverse data to enable business to have insights and take data driven decisions.
· Work closely with the business and Devops team data models, data dictionaries and vocabularies that enable effective data re-use over time.
· Work closely with the architecture community to ensure alignment of Data Management practices, Data Security, Data Modelling, Data Quality, Business Rules, and Business Analytics
· Contribute to and support a central process to establish and maintain key information about our data (e.g. data models, interfaces, data owners, security, etc.) to enable future streamlined data access and utilization
· Keep abreast of emerging trends in data integration and design technologies and work with the Information Architects to integrate them into target architectures, information management and data engineering practices as appropriate.
· Identify and triage data discrepancies with existing data when encountered through normal operations. Report and track discrepancies through remediation. As part of the analytical process and data re-use, develop actions and plans to address data-related issues, including those involving data quality, privacy, access control, and overall data anomalies
· Have good knowledge of Python/Scala, Azure tech stack – ADF, ADLS, storage explorer, blob store, databricks, Azure SQL database/DWH, Azure functions, Azure Devops (automated CI/CD), build and release pipelines and more.
· Very well worked in environment where Agile principles were followed, have worked in Scrum or Kanban.
· Proficient in Azure Tech stack and Python
· Degree in Computer Science, Information Technology, or the Life Sciences preferred
· Minimum of 3+ years relevant experience in a global IT organization
· Minimum of 2+ years in a Data Engineering or equivalent role
· Strong analytical skills in distilling use case requirements/needs into operational requirements
· Demonstrated understanding and application of principles and best practices of data integration and data quality management practices
· Not essential but preferred - knowledge of life sciences, retail, consumer healthcare
· Outstanding troubleshooting and problem solving skills
· Proven track record of quickly adapting skill set to meet the needs of changing technologies and business processes.
· Excellent verbal and written communication skills
· Excellent organization, influencing, and negotiation skills