Data Engineer

We are Seeking a Data Engineer to join a high-impact data platform team building scalable, cloud-native data pipelines for enterprise analytics and advanced data processing.This role is focused on hands-on development of distributed data pipelines, working with large-scale datasets, and designing reliable ingestion and transformation frameworks on AWS.Key ResponsibilitiesDesign and build end-to-end data pipelines from ingestion to analytics-ready datasetsDevelop Spark/PySpark-based ETL pipelines for large-scale batch processingImplement data workflows using AWS services such as S3, Glue, EMR, Lambda, and RedshiftBuild and maintain raw, enriched, and curated data layers in a data lake architectureOptimize pipelines for performance, scalability, and cost efficiencyImplement data validation, quality checks, and monitoring frameworksTroubleshoot distributed data processing issues and pipeline failures in productionCollaborate with cross-functional teams to deliver high-quality data solutionsRequired SkillsStrong experience in Python, SQL, and PySpark/SparkHands-on experience with AWS data services (S3, Glue, EMR, Lambda, Redshift)Experience building and maintaining large-scale ETL/ELT pipelinesSolid understanding of distributed data processing and performance tuningExperience with workflow orchestration tools (Airflow, etc.)Strong troubleshooting skills in production data environmentsIdeal Candidate7+ years of experience in data engineeringStrong hands on individual contributorComfortable working with large scale distributed systemsAbility to explain and troubleshoot real production pipelines