AWS L3 Support

Key Skills & Expertise

·AWS Core Services: S3, Redshift, Glue, Athena, Lake Formation, IAM

·Data Engineering / ETL:

·Building and optimizing ETL pipelines

·Data ingestion, transformation & orchestration using AWS Glue (PySpark/Python)

·Working with structured/semi-structured telecom datasets (CDRs, network logs, subscriber data)

Data Lake Technologies:

·Expertise in Apache Iceberg table format

·Schema evolution, partitioning, compaction & metadata management

·Query performance tuning with Athena & Redshift Spectrum

Redshift Expertise:

·Data modeling, distribution styles, sort keys

·Workload management (WLM)

·Performance optimization & troubleshooting

·Python:

·Automation scripts

·Data processing workflows

·Monitoring, debugging, validation scripts

AWS Support / Operations:

·Troubleshooting ETL failures, performance bottlenecks, pipeline issues

·Monitoring cloud workloads (CloudWatch, CloudTrail)

·Handling incidents, root-cause analysis (RCA), patching & releases

·Cost optimization and resource usage tracking

·Data quality checks for telecom data pipelines

Roles & Responsibilities

·Provide L2/L3 support for AWS-based data platforms in the telecom domain.

·Maintain and enhance ETL pipelines built on Glue + Iceberg + Athena + Redshift.

·Monitor production jobs, fix failures, optimize queries, and ensure SLA adherence.

·Develop automation for operational workflows using Python.

·Collaborate with data architects, business teams, and network teams for data requirements.

·Implement best practices for data governance, security, and cost management.

·Support migrations from legacy systems to AWS-native data lakes or Redshift.

Ideal Candidate Profile

·3–10+ years of experience in AWS Data Engineering / Support Engineering.

·Strong telecom domain understanding.

·Hands-on with Iceberg, Athena, Glue (PySpark), Python, Redshift, S3, ETL frameworks.

·Strong troubleshooting mindset and ability to work in 24×7 or rotational support environments (if required).