AWS Data Engineer

Talent Acquisition Executive @Amps Tek _ Sourcing Top Talents _ (UK & Europe)

Position type: Permanent (Onsite)

We are seeking an experienced AWS Data Engineer with strong expertise in ETL pipelines, Redshift, Iceberg, Athena, and S3 to support large‑scale data processing and analytics initiatives in the telecom 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.

• 1. ETL/ELT Pipelines
  • Design, develop, and maintain ETL/ELT pipelines using AWS‑native services (Glue, Lambda, EMR, Step Functions).
  • Implement data ingestion from telecom systems such as OSS/BSS, CDRs, mediation systems, CRM, billing, and network logs.
  • Optimize ETL workflows for large‑scale telecom datasets (high volume, high velocity).
• 2. Data Warehousing (Redshift)
  • Build and manage scalable Amazon Redshift clusters for reporting and analytics.
  • Create and optimize schemas, tables, distribution keys, sort keys
    , and workload management.
  • Implement Redshift Spectrum to query data in S3 using external tables.
• 3. Data Lake & Iceberg
  • Implement and maintain Apache 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).
• 4. Querying & Analytics (Athena)
  • Develop and optimise Athena 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.
• 5. Storage (S3) & Data Lake Architecture
  • Design secure, cost‑efficient S3 data lake structures (bronze/silver/gold zones).
  • Implement data lifecycle policies, versioning, and partitioning strategies.
  • Ensure data governance, metadata quality, and security (IAM, Lake Formation).
• 6. Telecom Domain Expertise
  • Understand telecom‑specific datasets such as network KPIs (4G/5G tower logs) and billing & revenue assurance.
  • Build models and pipelines to support network analytics, customer 360, churn prediction, fraud detection, and more.
• 7. 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.
• 8. Dev Ops & CI/CD (Preferred)
  • Use Git, Code Pipeline, Terraform/Cloud Formation for infrastructure and deployments.
  • Automate pipeline deployment and monitoring.

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

• Knowledge of AWS Lake Formation
  , Kafka/Kinesis
  , Airflow
  , or Delta/Apache Hudi
  .
• Experience with ML workflows in telecom (churn, network prediction).
• Exposure to 5G network data models
  .

Seniority level: Mid‑Senior level

Employment type: Full‑time

Job function: Information Technology

Thanks and Regards,

Schiffer Felix

Talent Acquisition Executive | UK & Europe

Ampstek Services Limited

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