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

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