Job Title: Data Engineer (4 Years Experience)Location: Pan IndiaJob Type: Full-Time Experience: 4 YearsNotice Period: Immediate to 30 days preferredJob Summary:We are looking for a skilled and motivated Data Engineer with over 4 years of experience in building and maintaining scalable data pipelines. The ideal candidate will have strong expertise in AWS Redshift and Python/PySpark with exposure to AWS Glue Lambda and ETL tools being a plus. You will play a key role in designing robust data solutions to support analytical and operational needs across the Responsibilities:Design develop and optimize large-scale ETL/ELT data pipelines using PySpark or and manage data models and workflows in AWS closely with analysts data scientists and stakeholders to understand data requirements and deliver reliable data validation cleansing and transformation to ensure high data and maintain automation scripts and jobs using Lambda and Glue (if applicable).Ingest transform and manage data from various sources into cloud-based data lakes (e.g. S3).Participate in data architecture and platform design pipeline performance troubleshoot issues and ensure data data workflows processes and infrastructure Skills:4 years of hands-on experience as a Data proficiency in AWS Redshift including schema design performance tuning and SQL in Python and PySpark for data manipulation and pipeline working with structured and semi-structured data (JSON Parquet etc.).Deep knowledge of data warehouse design principles including star/snowflake schemas and dimensional to Have:Working knowledge of AWS Glue and building serverless ETL with AWS Lambda for lightweight processing and to ETL tools like Informatica Talend or Apache with workflow orchestrators (e.g. Airflow Step Functions).Knwledge of DevOps practices version control (Git) and CI/CD Qualifications:Bachelor degree in Computer Science Engineering or related certifications (e.g. AWS Certified Data Analytics Developer Associate) are a plus.