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Big Data Engineer

1 month ago

Hyderabad, India People Prime Worldwide Full time

About the Company Our client is a trusted global innovator of IT and business services, present in 50+ countries. They specialize in digital & IT modernization, consulting, managed services, and industry-specific solutions. With a commitment to long-term success, they empower clients and society to move confidently into the digital future. Position: Data Engineer Experience: 6+ Years Location: Hyderabad Employment Type: Full-time About the Role We are looking for a highly skilled Data Engineer with 6+ years of experience in designing and building scalable data pipelines, big data processing solutions, and cloud-based data platforms. The ideal candidate will have strong expertise in Big Data technologies, PySpark, Python, AWS, and Snowflake , and will work closely with data architects, analysts, and business stakeholders to deliver efficient, reliable, and high-performance data solutions. Key Responsibilities Design, develop, and maintain scalable and high-performance ETL/ELT pipelines using PySpark, Python, and SQL. Build and optimize Big Data processing workflows using Spark, Hive, and other distributed data frameworks. Develop ETL/ELT frameworks and workflows on AWS cloud using services such as S3, Glue, EMR, Lambda, Step Functions, and Redshift. Implement and maintain enterprise-grade Snowflake data models, warehouses, data sharing, and performance tuning. Collaborate with data architects to design end-to-end data architecture, ensuring scalability, security, and reliability. Perform data ingestion, transformation, quality validation , and metadata management across various structured and unstructured data sources. Build CI/CD pipelines for data applications using tools like Git, Jenkins, or AWS CodePipeline. Monitor and optimize data pipelines for cost efficiency, performance, and reliability. Troubleshoot production issues and implement solutions for long-term stability and scalability. Ensure compliance with data governance, security best practices, and industry standards. Required Skills & Qualifications 6+ years of hands-on experience as a Data Engineer or similar role. Strong proficiency in PySpark , Spark SQL , and Big Data processing frameworks. Advanced programming skills in Python (data processing, automation, modular coding). Deep experience with AWS cloud services (S3, EMR, Glue, Lambda, IAM, Redshift, Athena). Hands-on experience working with Snowflake —data modeling, pipelines, SnowSQL, performance tuning. Strong SQL skills with experience in optimizing complex queries. Experience with workflow orchestration tools (Airflow / AWS Step Functions / Apache Oozie). Knowledge of DevOps practices, CI/CD, and version control (Git). Experience handling large-scale, distributed data systems in production environments. Strong understanding of data warehousing, ETL/ELT patterns, and best practices. Nice-to-Have Skills Experience with streaming technologies (Kafka, Kinesis). Knowledge of infrastructure-as-code (Terraform / CloudFormation). Familiarity with data catalog and governance tools (AWS Glue Data Catalog, Collibra, Alation). Exposure to ML data pipelines or MLOps frameworks.