Data Architect

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.