- Architect and deploy scalable data processing frameworks using PySpark to ensure high-throughput data transformation for enterprise-level applications.

- Lead the end-to-end development lifecycle of cloud-native solutions on AWS, optimizing infrastructure for performance, security, and cost-efficiency.

- Mentor junior engineers through code reviews and technical guidance to foster a culture of high-quality software development and engineering best practices.

- Collaborate with product managers and data scientists to translate complex business problems into modular, maintainable technical specifications.

Job Requirements :

Primary Skills (Non-Negotiable Skills) :

- Python

- REST

- SQL (specially, DB Performance Tuning/Joins/Nested Queries, preferable PostgreSQL)

- Spark

- Any ETL Tool (preferably, AWS Glue)

- Any Cloud (preferably, AWS)

- Core Java, knowledge of shell scripting.

Secondary Skills (Good to have) :

- Any MQ (preferably, ActiveMQ or RabbitMQ)

- Any NoSQL Datasource

- Spring Boot, microservices

- XML, XSLT Transformations.

- Experience with modern development patterns like microservices and serverless.

- Core AWS technologies IAM, VPC, EC2, S3, etc.

- More AWS technologies Lambda, ECS, Batch, RDS, API Gateway, etc.

- Estimations.

- Experience with Git / GitHub for source control management.

- Understanding of Test Driven and/or Behavior Driven Development.

- Understanding working in Linux/Unix environment.

Behavioral Skills :

- Experience in working closely with Business Analysts to understand requirements and translate into technical solutions.

- Experience in leading a team of 3- 4 senior developers and developers. Good design and troubleshooting skills.

- Experience working with remote/offshore team and International Customer team.

- Can-do attitude.

- Self-starting, motivated to learn.

- Good analytical skills, good communication skills.

- Attention to details, focus.