FIND_THE_RIGHTJOB.
Lead Data Engineering (Data Platform)
JOB_REQUIREMENTS
Hires in
Not specified
Employment Type
Not specified
Company Location
Not specified
Salary
Not specified
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:
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:
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
© 2025 Qureos. All rights reserved.