AWS Data Engineer – L1/L2

Job Title: AWS Data Engineer – L1/L2 Support Role

Job Overview

We are seeking a Level 1/2 AWS Data Engineer to join our dynamic team. This role is responsible for monitoring, troubleshooting, and optimizing AWS-based data pipelines. The ideal candidate will work with AWS Glue, Lambda, Step Functions, and other AWS data services to investigate job failures, re-run ETL jobs, and ensure data integrity. This position requires strong analytical thinking, problem-solving skills, and a solid understanding of AWS data engineering best practices.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Information Technology, or a related field.

• Up to 1+ year of experience in AWS-based data engineering.

• Hands-on experience with AWS Glue, S3, Athena, Lambda, Step Functions, and CloudWatch.

• Strong Python (Pandas, Boto3) and SQL skills for data querying and processing.

• Familiarity with PySpark and ETL development is a plus.

• Basic knowledge of AWS IAM, security policies, and access control.

• Experience in monitoring and debugging AWS Glue jobs, Step Functions, and Lambda logs.

• Hands-on experience with Data Lake, Delta Lake, and Lakehouse architectures.

• Strong analytical and problem-solving skills to diagnose and resolve data processing failures.

• Ability to work independently while collaborating effectively with cross-functional teams.

• AWS certification such as AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect Associate (preferred but not mandatory).

Key Responsibilities

• Monitor, troubleshoot, and support AWS data pipelines (Glue, Lambda, Step Functions, S3, Athena, Redshift, Airflow).

• Investigate job failures, analyze CloudWatch logs, and take corrective actions to ensure pipeline continuity.

• Re-run failed jobs and retry data ingestion processes while maintaining data consistency.

• Assist in debugging Glue ETL scripts, Athena queries, and Lambda functions used for data transformations.

• Collaborate with L2/L3 engineers and data architects to escalate and resolve complex issues.

• Optimize data processing jobs by applying best practices in partitioning, bucketing, and indexing.

• Maintain documentation of troubleshooting steps, common issues, and resolutions.

• Ensure compliance with AWS security best practices (IAM roles, policies, and access controls).

• Participate in incident response and data recovery procedures as required.

• Provide technical support for production data pipelines, ensuring SLAs are met.