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.