Responsibilities:

• Data Architecture:Develop and maintain a comprehensive data architecture, including data models, data flows, and data governance policies. Sharing best practice in cloud native data integration - security, scalability, latency ; point to point data feeds, GDPR, Governance, customer consent management etc
• Data Integration:Design and implement data integration strategies to consolidate data from various sources, such as vehicle telematics, manufacturing systems, and customer interactions.
• Data Warehousing and Data Lakes:Architect and manage data warehouses and data lakes to store and process large volumes of structured and unstructured data.
• Data Governance:Establish and enforce data governance policies to ensure data quality, security, and compliance with industry standards.
• Data Analytics:Collaborate with data scientists and analysts to enable advanced analytics and machine learning initiatives.
• Cloud Technologies:Leverage cloud platforms (e.g., AWS, Azure, GCP) to build scalable and cost-effective data solutions. Understanding of Cloud Platforms and how data can be leveraged/utilised in a could native environment. Understanding of Data Security in the context of the Cloud. Ability to Architect/previous experience in architecting data exchange in the context of the Enterprise, the front end and the Cloud ( in a cloud Native environment). Experience in usage of tools such as Power BI, AWS, GCP.
• Data Security and Privacy:Implement robust security measures to protect sensitive data and comply with relevant regulations.
• Data Visualization:Work with data visualization tools to create insightful dashboards and reports for business stakeholders.
• 360 degree customer data model- Ability to map CX journey with the data touchpoints and map these to the data model and create a 360 degree data model. Ability to understand the CX journeys for a mobile and online journey from login, to authentication 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, utilising the data points to build a view of customer behaviour; combine this with user data of the digital assets; use data to understand user behavioral patterns

Qualifications:

• Strong understanding of data architecture principles, data modeling techniques (e.g., dimensional modeling, data vault), and data warehousing concepts.
• Proficiency in SQL, Python, and other relevant programming languages.
• Experience with data integration tools (e.g., Informatica, Talend) and data warehousing tools (e.g., Snowflake, Redshift).
• Knowledge of cloud platforms (AWS, Azure, GCP) and cloud-native data technologies.
• Familiarity with data governance frameworks and data security best practices.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.
• A passion for electric vehicles and a desire to contribute to a sustainable future.

Preferred Qualifications:

• Experience in the automotive industry or a related field.
• Knowledge of IoT technologies and real-time data processing.
• Experience with machine learning and AI applications in the automotive domain.