Data Engineer

Data Engineer

Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL processes to migrate and deploy data across systems.

Must have skills: PySpark

Minimum 7.5 year(s) of experience is required. Educational Qualification: 15 years full time education.

As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand data requirements and provide innovative solutions to enhance data accessibility and usability.

Core Skills: Data Engineering with Python, Pyspark, SQL and AWS Experience:

• 6+ years of hands-on experience in Python-based data engineering
• Strong experience with PySpark / Apache Spark for large-scale data processing
• Experience with relational databases and NoSQL databases
• Hands-on experience with AWS services, including:
• AWS EMR / Glue
• AWS S3 / Step Functions / Lambda
• AWS RDS / DynamoDB/Athena/Crawlers
• Proficiency in Python scripting and basic shell scripting
• Strong experience in Terraform for infrastructure provisioning and automation
• Experience with data modeling, partitioning, and performance tuning
• Familiarity with CI/CD pipelines for data and cloud deployments

Key Responsibilities:

• Design, develop, and optimize data pipelines and ETL/ELT workflows using Python and PySpark
• Build and maintain distributed data processing frameworks on AWS
• Work with large-scale structured and semi-structured datasets
• Design and manage SQL and NoSQL databases to support analytics and operational workloads
• Deploy and manage data workloads using AWS Offerings
• Provision and manage cloud infrastructure using Terraform (Infrastructure as Code)
• Develop and maintain automation scripts using Python and shell scripting
• Ensure data quality, performance, reliability, and scalability of data pipelines
• Integrate data from multiple sources including APIs, databases, and streaming systems
• Monitor, troubleshoot, and optimize data processing jobs in production environments
• Collaborate with data scientists, analysts, DevOps, and cloud teams

Additional Information:

• The candidate should have minimum 7.5 years of experience in PySpark.
• This position is based at our Hyderabad office.
• A 15 years full time education is required.