ploy, and optimize data pipelines, lakes, and warehousing solutions that power real-time analytics, machine learning, and business intelligence across industries.

Role & Responsibilities

Design and implement scalable ETL/ELT pipelines using AWS Glue, Lambda, and Step Functions for batch and real-time data ingestion.
Build and maintain data lakes on S3 with proper partitioning, cataloging (Glue Data Catalog), and governance using IAM and Lake Formation.
Orchestrate data workflows via AWS MWAA or Step Functions, monitor pipeline health, and ensure SLA compliance.
Optimize Redshift or Snowflake (if integrated) for performance and cost using materialized views, distribution keys, and query tuning.
Implement data quality checks, lineage tracking, and alerting using CloudWatch, Athena, and custom Python scripts.
Collaborate with analytics and ML teams to deliver clean, curated datasets for dashboards and model training.

Skills & Qualifications

Must-Have
AWS Glue
Amazon S3
AWS Lambda
Amazon Redshift
Amazon Athena
Python
SQL
ETL/ELT
Preferred
AWS Step Functions
AWS MWAA
Apache Airflow

Benefits & Culture Highlights

Onsite collaborative environment with access to cloud certification sponsorships.
Direct exposure to enterprise-scale AWS data architectures and cross-functional teams.
Fast-paced, learning-driven culture with growth acceleration for high performers.

Skills: glue,aws,etl,athena,sql,python,cloud,amazon redshift,aws lambda

AWS Data Engineer