Aws Data Engineer

2 days ago

Ipswich, Suffolk, United Kingdom BULLIT MANAGEMENT SERVICES LIMITED Full time

Role Overview

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.

Key Responsibilities

1. Data Engineering & ETL Development

  • Design, develop, and maintain 
    ETL/ELT pipelines
     using AWS-native services (Glue, Lambda, EMR, Step Functions).
  • Implement data ingestion from telecom systems like 
    OSS/BSS, CDRs, mediation systems, CRM, billing, 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 optimize 
    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:

o   
CDR, xDR, subscriber data

o   
Network KPIs (4G/5G tower logs)

o   
Customer lifecycle & churn data

o   
Billing & revenue assurance

  • Build models and pipelines to support 
    network analytics, customer 360, churn prediction, fraud detection
    , etc.

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. DevOps & CI/CD (Preferred)

  • Use 
    Git, 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:

o   
AWS S3, Athena, Glue, Redshift, EMR/Spark

o   
Apache Iceberg

o   
Python/SQL

  • Experience in 
    telecom data pipelines
     and handling large-scale structured/semi-structured data.
  • Strong problem-solving, optimization, and debugging skills.

Good to Have 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
    .

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