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AWS Glue Data Engineer

Anywhere
full-time
Posted 9/2/2025
Direct Apply
Key Skills:
AWS Glue
PySpark
Python
SQL
AWS S3
Redshift
Athena
Lambda
Step Functions
Data Modeling
ETL Pipelines

Compensation

Salary Range

$120K - 160K a year

Responsibilities

Design, develop, and optimize large-scale ETL data pipelines using AWS Glue and related AWS data services.

Requirements

12+ years in data engineering with 5+ years on AWS cloud data services, strong AWS Glue and PySpark skills, data modeling expertise, and experience with AWS data lakes and warehouses.

Full Description

Job Title: AWS Glue Data Engineer Location: Fort Mill, SC or New York City, NY (Hybrid) Job SummaryWe are seeking a highly skilled AWS Glue Data Engineer to design, develop, and optimize large-scale data pipelines and ETL workflows on AWS. The ideal candidate will have strong expertise in AWS cloud-native data services, data modeling, and pipeline orchestration, with hands-on experience building robust and scalable data solutions for enterprise environments. Key Responsibilities Design, develop, and maintain ETL pipelines using AWS Glue, Glue Studio, and Glue Catalog. Ingest, transform, and load large datasets from structured and unstructured sources into AWS data lakes/warehouses. Work with S3, Redshift, Athena, Lambda, and Step Functions for data storage, query, and orchestration. Build and optimize PySpark/Scala scripts within AWS Glue for complex transformations. Implement data quality checks, lineage, and monitoring across pipelines. Collaborate with business analysts, data scientists, and product teams to deliver reliable data solutions. Ensure compliance with data security, governance, and regulatory requirements (BFSI preferred). Troubleshoot production issues and optimize pipeline performance. Required Qualifications 12+ years of experience in Data Engineering, with at least 5+ years on AWS cloud data services. Strong expertise in AWS Glue, S3, Redshift, Athena, Lambda, Step Functions, CloudWatch. Proficiency in PySpark, Python, SQL for ETL and data transformations. Experience in data modeling (star, snowflake, dimensional models) and performance tuning. Hands-on experience with data lake/data warehouse architecture and implementation. Strong problem-solving skills and ability to work in Agile/Scrum environments. Preferred Qualifications Experience in BFSI / Wealth Management domain. AWS Certified Data Analytics – Specialty or AWS Solutions Architect certification. Familiarity with CI/CD pipelines for data engineering (CodePipeline, Jenkins, GitHub Actions). Knowledge of BI/Visualization tools like Tableau, Power BI, QuickSight. Education Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field. Master’s degree preferred.

This job posting was last updated on 9/5/2025

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