Have 11+ years of demonstrable experience in the IT industry, working as a
Production Development
on successful enterprise scale applications or
projects implementing Big Data Lake architecture using AWS services/data pipelines

Must have
AWS Lambda, BDL(Hive and Trino), Glue, Spark, Data Pipelines, Dremio

Excellent understanding of sql, and rdbms using Oracle and Postgres.
Knowledge of Data Architecture, Data warehouse concepts, Dimensional Modelling
Some experience with a scripting language like Python
Knowledge of APIGEE
Uses best practice while programming, must be able to write superior quality code with excellent naming conventions
Should have over 5 years Experience in Data Architecture, Data warehouse concepts, Dimensional Modelling.
Should have worked on at least 1 Data Warehouse project in the past.
Development lifecycle experience.
Atleast 5 years of experience in SQL and AWS ETL design and development, following best practices for coding and performance tuning and iterative development approach (Must Have)
Strong technical skills in Database and scripting (Oracle and Postgres) (Must Have)
Needs to be able to understand the logical mapping and data models provided, design, and develop ETL mappings as per available patterns.
The developer needs to be familiar with agile development practice using ticketing tools
Should be able to respond to technical queries / requests from team members and customers
Have Good communication and presentation skills
Ability to multi task and liaise with multiple stakeholders
Ability to identify process improvement opportunities
Adaptability to change Knowledge of processes & development best practice
Be a self-starter and take independent responsibilities proactively.
Demonstrate good interpersonal skills to communicate effectively with team members and all the stakeholders of the project.
Closely working with Business Stakeholders , Development team and Infrastructure teams on requirements, clarifications and issues to sort out the bottlenecks in quality deliverables on time.
Builds knowledge on emerging tools, techniques and technologies.