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Tier-1 employer, popular data engineer title, metro location and broad AWS skillset raise competition.
AWS data engineering skills are highly transferable, with telecom domain knowledge as a modest advantage.
Explicit 7+ years requirement plus mandatory AWS Glue/Spark/Redshift skills makes shortlisting strict.
Design, develop, and maintain scalable ETL and data pipelines using AWS Glue, Apache Spark, Amazon Redshift, and related AWS services to support data-driven decision making.
Build and optimize data warehousing and data lake solutions for analytical and operational requirements, including creating data models and ensuring data quality.
Collaborate with global cross-functional teams to develop data products, automate processes, manage deployments using GitHub and CI/CD, and contribute to continuous improvement initiatives.
7 to 10+ years of experience in Data Warehousing and Data Engineering.
Strong hands-on expertise with AWS Glue, Python, Apache Spark, Amazon Redshift, Amazon Athena, and Apache Iceberg.
Experience with GitHub, CI/CD practices, API integrations, and JSON processing.
Work Experience Required: 7 to 10+ years in relevant data engineering roles.
Experienced in designing and supporting enterprise-scale ETL pipelines within AWS-native data engineering environments.
Comfortable working with global and multicultural teams, managing stakeholders across multiple markets.
Familiarity or interest in telecom business processes and data domains is a plus but not mandatory.