Aws Data Engineer (Telecom Domain)

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We are seeking an experiencedAWS Data Engineer with strong expertise inETL pipelines, Redshift, Iceberg, Athena, and S3 to support large-scale data processing and analytics initiatives in thetelecom domain . The candidate will work closely with data architects, business analysts, and cross‑functional teams to build scalable and efficient data solutions supporting network analytics, customer insights, billing systems, and telecom OSS/BSS workflows.

Key Responsibilities

• Design, develop, and maintainETL/ELT pipelines using AWS‑native services (Glue, Lambda, EMR, Step Functions).
• Implement data ingestion from telecom systems likeOSS/BSS, CDRs, mediation systems, CRM, billing, network logs .
• Optimize ETL workflows for large‑scale telecom datasets (high volume, high velocity).

Data Warehousing (Redshift)

• Build and manage scalableAmazon Redshift clusters for reporting and analytics.
• Create and optimizeschemas, tables, distribution keys, sort keys , and workload management.
• Implement Redshift Spectrum to query data in S3 using external tables.

Data Lake & Iceberg

• Implement and maintainApache Iceberg tables on AWS for schema evolution and ACID operations.
• Build Iceberg‑based ingestion and transformation pipelines using Glue, EMR, or Spark.
• Ensure high performance for petabyte‑scale telecom datasets (CDRs, tower logs, subscriber activity).

Querying & Analytics (Athena)

• Develop and optimizeAthena queries for operational and analytical reporting.
• Integrate Athena with S3/Iceberg for low‑cost, serverless analytics.
• Manage Glue Data Catalog integrations and table schema management.

Storage (S3) & Data Lake Architecture

• Implement data lifecycle policies, versioning, and partitioning strategies.
• Ensure data governance, metadata quality, and security (IAM, Lake Formation).

Telecom Domain Expertise

• Understand telecom‑specific datasets such as:
• Network KPIs (4G/5G tower logs)
• Billing & revenue assurance
• Build models and pipelines to supportnetwork analytics, customer 360, churn prediction, fraud detection , etc.

Performance Optimization & Monitoring

• Tune Spark/Glue jobs for performance and cost.
• Monitor Redshift/Athena/S3 efficiency and implement best practices.
• Perform data quality checks and validation across pipelines.

DevOps & CI/CD (Preferred)

• UseGit, CodePipeline, Terraform/CloudFormation for infrastructure and deployments.
• Automate pipeline deployment and monitoring.

Required Skills

• 3–10 years experience in data engineering.
• Strong hands‑on experience with:
• Python/SQL
• Telecom data pipelines and handling large‑scale structured/semi‑structured data.
• Strong problem‑solving, optimization, and debugging skills.

Good to Have Skills

• Knowledge ofAWS Lake Formation ,Kafka/Kinesis ,Airflow , orDelta/Apache Hudi .
• Experience with ML workflows in telecom (churn, network prediction).

Seniority level

• Mid‑Senior level

Employment type

• Full‑time

Job function

• Information Technology

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