Sr Spec , IT-ETL Developer

Overview

Design, develop, and implement enterprise-scale data integration and data engineering solutions. Build scalable data pipelines, modernize data platforms, integrate enterprise applications, and support business analytics through reliable and high-performing data solutions.

What you'll do

• Design, develop, and maintain end-to-end data integration and engineering solutions.
• Lead the complete project lifecycle including requirements analysis, solution design, development, testing, deployment, and production support.
• Build and optimize scalable ETL/ELT pipelines for data ingestion, transformation, and loading.
• Develop robust data processing frameworks using PySpark and Python.
• Design and optimize complex SQL queries and data transformations.
• Develop and support integrations using REST APIs and modern integration patterns.
• Implement and maintain cloud-based data solutions leveraging AWS services and Snowflake.
• Ensure data quality, performance, scalability, and reliability across data platforms.
• Collaborate with business stakeholders, architects, and application teams to deliver effective data solutions.
• Troubleshoot production issues and provide timely resolutions.
• Follow data governance, security, and compliance standards.
• Mentor junior team members and contribute to data engineering best practices.

What you'll need

• Strong hands-on experience in PySpark development for large-scale distributed data processing.
• Experience developing and optimizing Spark applications for high-volume data workloads.
• Knowledge of Spark DataFrames, Spark SQL, performance tuning, and cluster optimization.
• Strong programming skills in Python.
• Experience building reusable frameworks, data pipelines, and automation solutions.
• Knowledge of object-oriented programming and data processing libraries.
• Advanced SQL development and performance tuning.
• Strong experience writing complex queries, stored procedures, and data transformations.
• Good understanding of data modeling and data warehousing principles.
• Hands-on experience with AWS services including Amazon S3, AWS Glue, AWS Lambda, Amazon EMR, AWS Step Functions, Amazon RDS, and Amazon CloudWatch.
• Strong experience with Snowflake Data Cloud.
• Knowledge of cloud-based data architecture and data lake implementations.
• Strong understanding of ETL/ELT concepts and data integration patterns.
• Experience in end-to-end implementation of data engineering solutions.
• Strong knowledge of data warehousing, data modeling, and data migration concepts.
• Experience with Git and version control systems.
• Experience with CI/CD and DevOps practices.
• Experience with Agile and Scrum methodologies.

Nice to have

• Experience developing and supporting ETL workflows using Informatica PowerCenter and/or Informatica Intelligent Cloud Services (IICS).
• Knowledge of data integration, transformation, and migration processes.
• Experience with IBM DataStage development and support.
• Knowledge of Parallel Jobs, ETL workflows, performance tuning, and migration initiatives.
• Experience in ETL modernization projects is an added advantage.

Details

• Location: Bangalore, Karnataka.