AWS Data Engineer

Walk-in Drive for AWS Data Engineer | Exciting Career Opportunities! &A1; 3 cities | 1 day Walk-in Interview Drive Date: 22-Aug-26 (Saturday) ⏰Registration Time: 9:00 AM to 12:30 PM Experience: 5 to 15 years Locations: #Chennai Tata Consultancy Services : Siruseri Campus is located at Plot No. 1/G1, SIPCOT IT Park, Navalur Post, Siruseri, Chennai, Tamil Nadu 603103 #Bangalore Tata Consultancy Services: Think Campus 42, 45-P, Hosur Rd, Phase II, Konappana Agrahara, Karnataka 560100 #Pune Tata Consultancy Services: Sahyadri Park 2, Interview Bay, Plot No. 2 & 3, Phase 3, Rajiv Gandhi Infotech Park, Hinjewadi, Pune, Maharashtra, 411057 Job Title: AWS Data Engineer (Python & PySpark) Experience: 6 – 12 Years Location: Pune / Bangalore / Hyderabad / Chennai / Mumbai Job Description: We are looking for an experienced AWS Data Engineer with strong expertise in Python, PySpark, and AWS Data Services to design, develop, and optimize scalable data pipelines and cloud-based data engineering solutions. The ideal candidate should have hands-on experience in developing large-scale data processing applications, data lake implementations, and ETL/ELT frameworks on AWS. [TCS_JD_Tem...Developer | Word] , [TCS_JD_Tem...pr aws TRP | Word] Must-Have Skills: Strong programming experience in Python Hands-on expertise in PySpark Experience with AWS services such as: S3 EMR Glue Lambda IAM Athena Redshift Strong SQL and Data Warehousing concepts Experience in building ETL/ELT pipelines Data Lake/Data Warehouse implementation experience Git/GitHub version control Performance tuning and optimization of Spark applications Understanding of Agile development methodologies Good-to-Have Skills: Databricks Apache Airflow dbt Snowflake Terraform Kafka CI/CD Pipelines Docker/Kubernetes Roles & Responsibilities: Design, develop, and maintain scalable data pipelines using Python and PySpark. Build and optimize ETL/ELT processes on AWS cloud platforms. Develop batch and real-time data processing solutions. Work with large-scale structured and unstructured datasets. Create and maintain Data Lakes and Data Warehouse solutions. Perform data quality validation, monitoring, and troubleshooting. Collaborate with business stakeholders, architects, and development teams to gather requirements and deliver data solutions. Optimize Spark jobs for performance, scalability, and cost efficiency. Participate in code reviews and ensure adherence to coding standards. Support production deployments and resolve critical incidents. Relevant Experience: 6–12 years of overall IT experience. Minimum 4+ years of hands-on experience in Python and PySpark development. Experience in AWS-based data engineering projects. Strong exposure to Data Warehousing and Data Lake architectures. [TCS_JD_Tem...Databricks | Word] , [TCS_JD_Tem...Developer | Word] Education: BE / B.Tech / MCA / M.Tech or equivalent.