As a Data Engineer, you will be part of a dynamic team of data engineers and being responsible for technical design, implementation, optimizing and maintenance of data engineering solution components for our customers. Your will be required to have strong hands-on experience in implementing complex data engineering solutions on AWS, with a good understanding of data warehouse, data lake and lake-house architecture patterns.

Requirements :

- 3 - 8 years of hands-on experience in design, development and implementation of data engineering solutions

- Good understanding of database concepts and strong hands-on experience in SQL development, including

performance tuning and query optimization

- Good understanding of programming concepts with Python

- Strong hands-on experience in implementing data pipelines using PySpark or Spark Scala

- Must have an understanding of streaming data pipelines for near real-time analytics

- Hands-on experience and good understanding of AWS services for data engineering, including AWS Glue, Lambda, Step Functions, Amazon Redshift, EMR, Amazon Kinesis etc.

- Good understanding and experience working with at-least one NoSQL database

- Good understanding of modern data architecture patterns and industry trends in data engineering space

- Good understanding of data governance concepts for data platforms and analytical solutions

- Experience with version control tools like Git for managing version control for source code

- Experience with DevOps processes, including experience implementing CI/CD pipelines for data engineering solution components

- Strong analytical and problem-solving skills.

- Excellent communication and collaboration skills

Good to Have :

- Certifications on AWS platform, preferably related to Data Engineering

- Experience working with Amazon AppFlow, EKS, API Gateway, NoSQL database services

- Good understand and experience working with BI/visualization tools like Tableau / PowerBI