Nissan is a pioneer in Innovation and Technology. With a focus on Mobility, Operational Excellence, Value to our Customers and Electrification of vehicles, you can expect to be part of a very exciting journey here at Nissan.
Nissan is going after a massive Digital Transformation backed by leading technologies across the organization globally. We are committed to building a diverse, entrepreneurial organization, and our current team is a strong evidence of that. Our people are what drive the business forward. At Nissan Digital, you will be part of a dynamic team with ample opportunities to grow and make a difference.
Role Overview
The Data Platform Lead will be responsible for driving the overall strategy, governance, and operational excellence of the enterprise data platform. This role involves leading vendor-based data engineering and architecture teams, ensuring efficient resource planning, and overseeing critical platform initiatives.
Key Responsibilities:
Lead and manage vendor Data Engineering and Architecture teams, including task allocation and resource planning.
Serve as the primary owner of the Data Platform strategy and its roadmap.
Oversee Data Platform reporting activities, including system go-lives, KPI tracking, usage insights, and FinOps monitoring.
Act as the subject matter expert for the Data Platform ecosystem (Snowflake, AWS, Glue, etc.).
Define and evolve long-term platform strategy in alignment with business and technology goals.
Collaborate closely with Delivery and Operations Leads to address and prioritize business requirements.
Own the DRM process and establish future Data Catalogue and data-modelling standards, ensuring robust data architecture practices.
Skills and Qualifications:
The ideal candidate should have worked on end-to-end data warehousing, data lake solutions in cloud platforms (AWS). The candidate should have the following skills sets:
Strong data engineering (ETL) experience in cloud preferably in AWS.AWS Certification (developer/Devops/SA) preferred.
Excellent understanding of distributed computing paradigm.
Should have excellent experience in data warehouse and data lake implementation.
Should have excellent experience in Relational databases, ETL design patterns and ETL development.
Should have excellent experience in CICD frameworks and container based deployments.
Should have excellent programming and SQL skills.
Should have good exposure to No-SQL and Big Data technologies.
Should have strong implementation experience in all the below technology areas (breadth) and deep technical expertise in some of the below technologies:
Data integration/Engineering – ETL tools like Talend ETL, AWS Glue etc. Experience in Talend Cloud ETL will be plus.
Datawarehouse - Snowflake and or AWS Redshift. Experience in Snowflake cloud DWH would be an advantage.
Data modelling – Dimensional & transactional modelling using RDBMS, NO-SQL and Big Data technologies.
Programming - Java/Python/Scala and SQL.
Data visualization – Tools like Tableau, Quicksight.
Master data management (MDM) – Concepts and experience in tools like Informatica & Talend MDM.
Exposure to Big data – Hadoop eco-system, AWS EMR.
Exposure to Big Data processing frameworks – Kinesis, Spark & Spark streaming
Demonstrate strong analytical and problem solving capability
Good understanding of the data eco-system, both current and future data trends.
Should be a go to person for the above technologies