Lead Data Engineering (Data Platform)

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