Apply

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.

The Role:

We are looking for passionate and seasoned senior big data architect to build next generation cloud data platforms(Datalake,DWH etc.) and business intelligence solutions in cloud (AWS preferred) using big data technologies. The candidate would be required to understand and gather the data warehouse / data lake requirements, architect, design and implement timely solutions for the business needs. The candidate should be able to own and be responsible for the complete architecture of multiple data projects / products at the same time.

Responsibilities:

Senior big data architect need to architect, design and implement data platforms (datalake, DWH, ODS etc.) and frameworks (Streaming, ML, IOT analytics etc.) in cloud using various big data technologies.

The primary responsibilities include:

Own and drive the architecture for multiple projects / products at the same time considering the global roll outs
Manage global roll outs of data projects / products working with various stakeholders
Choose the right architecture that would solve the business problems
Lead a team of data engineers and senior / lead engineers by mentoring and guiding them
Communicate and translate the technical solution to the team and other stakeholders
Architect, design and implement various components of data pipeline that include data integration, storage, processing and analysis of business data
Drive re-use initiatives and promote re-use culture within the team
Collaborate with application development and support teams on various IT projects
Develop complex modules and proof of concepts
Lead and drive performance optimization efforts
Define standards and guidelines for the project and ensure team is following those
Assist in setting strategic direction for database, infrastructure and technology through necessary research and development activities
Automation should be a key driver and the development & testing should be automated through frameworks / tools
Monitoring performance and advising any necessary infrastructure changes through capacity planning & sizing exercises
Work with various vendors like cloud providers and consultants to deliver the project
Define non-functional requirements and make sure that the solution adhere to the requirements
Define best practices of agile & DevOps while implementing solutions

Skills and Qualifications:

The ideal candidate should have architected multiple end-to-end data warehousing / data lake and / or business intelligence solutions in the past using big data technologies. The candidate should have the following skills sets:

Excellent experience in cloud data platforms and data services is a must. AWS certification is preferred.
Excellent understanding of distributed computing paradigm
Excellent programming background using Java, Scala or Python
Should have good knowledge in data warehouse / data lake technology and business intelligence concepts
Good understanding of Lambda architecture
Should have strong implementation experience in three or more tools from any of the below technologies:
Data integration – Ingestion mechanism like Kinesis,Kafka, NiFi, AWS Glue
Experience in cloud data eco-system, specifically with AWS. Experience in AWS data components like S3, Glue,EMR,Redshift & RDS, managed services like Aurora & Athena are desirable
Data storage - Relational, NO-SQL and big data storage. Distributed data warehouse solutions like Snowflake
Big data – Hadoop eco-system, HDFS, Distributions like EMR/Cloudera / Hortonworks, Pig and HIVE
Data processing frameworks – Spark & Spark streaming or Databricks
Hands-on experience with multiple databases like PostgreSQL, Snowflake, Oracle, MS SQL Server, NOSQL (HBase / Cassandra, MongoDB), is required
Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming
Good conceptual knowledge in data modelling using dimensional & transactional modelling
Demonstrate strong analytical and problem solving capability
Good understanding of the data eco-system, both current and future data trends
Familiarity with other cloud providers like Microsoft Azure and Google GCP would be added advantage
Experience in architecting solutions in a cloud agnostic / vendor agnostic way would be desirable
Exposure to advanced data analytics using machine learning techniques for various business use cases would be required
Exposure to data visualization techniques and analytics using tools like Tableau would be required
Minimum 12-16 years of experience in the data engineering space using above technologies with owning number of complex & high volume data projects / products with global roll outs as an architect is mandatory.