AWS Data Engineer – L1/L2 Support Role

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

Job Overview

We are looking for a Level 1/2 AWS Data Engineer to join our team. In this role, you will be responsible for monitoring, troubleshooting, and optimizing AWS-based data pipelines. You 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. You will be part of a fast-paced environment that requires analytical thinking, problem-solving skills, and an understanding of AWS data engineering best practices.

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 data pipeline continuity.

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

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

- Work closely 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 while ensuring SLAs are met.

Qualifications

- Bachelor’s degree in Computer Science, Data Science, Information Technology, or 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).