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Dunnhumby
,
London, Greater London
Technical Account Associate
Overview
Job Description
dunnhumby is looking for a talented Technical Account Associate! You will support contact with clients on the technical implementation of our data platform and/or software products in order to provide a high quality and professional delivery of our products and services. What you'll be doing: Support senior team members with data exploration assessment and audit to fully understand client data/systems. Support in answering data related inquiries from both internal and client stakeholders: use subject matter experts across the team and beyond to handle and manage the most complex questions. Use data knowledge to support and suggest the best options to outline the data roadmap and resolve data issues/problems. Support the documentation of data requirements to assure roadmap/delivery plans. Support the resolution of data issues with client data providers (in conjunction with the data management team). Technical Pre-Sales - Work with dunnhumby Client Leadership and Analysis teams to understand proposed scope of work to ensure dunnhumby data solution and products as well as client IT are able to meet requirements. Feedback in to the overall product deployment process design and core technology roadmap based on findings from client interfaces. What you'll need: * Bachelor's degree or equivalent in Information Technology or related field. * Some experience querying and investigating data in any flavor of SQL. * Industry Standard Configuration and Release / Deployment Process * Data Architecture & Modelling * Cloud Infrastructure, Management and Hosting * SQL A plus if you also have: * Master's degree in Business, Information Technology, or Analytics. * Experience within Commercial IT & analytics or a Technical Consulting company. * Some experience working in distributed computing * Experience with specific Cloudera and/or HortonWorks implementations * Experience with Cluster frameworks * Experience with PaaS * Experience with modern and traditional data warehousing and data processing technologies and concepts (Hadoop, PySpark, Hive, RDBMS). * Experience with data engineering concepts and technologies.