Responsibilities: Data Architecture: Develop andmaintain a comprehensive data architecture, including data models,data flows, and data governance policies. Sharing best practice incloud native data integration - security, scalability, latency ;point to point data feeds, GDPR, Governance, customer consentmanagement etc Data Integration: Design and implement dataintegration strategies to consolidate data from various sources,such as vehicle telematics, manufacturing systems, and customerinteractions. Data Warehousing and Data Lakes: Architect and managedata warehouses and data lakes to store and process large volumesof structured and unstructured data. Data Governance: Establish andenforce data governance policies to ensure data quality, security,and compliance with industry standards. Data Analytics: Collaboratewith data scientists and analysts to enable advanced analytics andmachine learning initiatives. Cloud Technologies: Leverage cloudplatforms (e.g., AWS, Azure, GCP) to build scalable andcost-effective data solutions. Understanding of Cloud Platforms andhow data can be leveraged/utilised in a could native environment.Understanding of Data Security in the context of the Cloud. Abilityto Architect/previous experience in architecting data exchange inthe context of the Enterprise, the front end and the Cloud ( in acloud Native environment). Experience in usage of tools such asPower BI, AWS, GCP. Data Security and Privacy: Implement robustsecurity measures to protect sensitive data and comply withrelevant regulations. Data Visualization: Work with datavisualization tools to create insightful dashboards and reports forbusiness stakeholders. 360 degree customer data model - Ability tomap CX journey with the data touchpoints and map these to the datamodel and create a 360 degree data model. Ability to understand theCX journeys for a mobile and online journey from login, toauthentication to product selection to checkout. Data Monetisation: Experience or ability to help the clients to monetise data.Ability to understand the data inputs and data outputs, utilisingthe data points to build a view of customer behaviour; combine thiswith user data of the digital assets; use data to understand userbehavioral patterns Qualifications: Strong understanding of dataarchitecture principles, data modeling techniques (e.g.,dimensional modeling, data vault), and data warehousing concepts.Proficiency in SQL, Python, and other relevant programminglanguages. Experience with data integration tools (e.g.,Informatica, Talend) and data warehousing tools (e.g., Snowflake,Redshift). Knowledge of cloud platforms (AWS, Azure, GCP) andcloud-native data technologies. Familiarity with data governanceframeworks and data security best practices. Strong analytical andproblem-solving skills. Excellent communication and collaborationskills. A passion for electric vehicles and a desire to contributeto a sustainable future. Preferred Qualifications: Experience inthe automotive industry or a related field. Knowledge of IoTtechnologies and real-time data processing. Experience with machinelearning and AI applications in the automotivedomain.
