AWS Data Engineer ( EMR Exp) - W2 Contract

Data Engineer Telecom

Location: Denver, CO Onsite
Interview Mode: Virtual + In-Person
Industry: Telecom
Job Type: Contract

Required Skills: ETL, SQL, AWS, Apache Spark, AWS EMR

Job Description:

We are looking for an experienced Data Engineer to support data engineering initiatives for a leading Telecom client. The candidate will be responsible for developing and maintaining scalable data pipelines, processing large datasets, and supporting data integration and analytics requirements.

Key Responsibilities:

• Design, develop, and maintain ETL/ELT data pipelines for large-scale telecom data.
• Develop complex and optimized SQL queries for data extraction, transformation, and validation.
• Build and maintain data processing solutions using Apache Spark.
• Work extensively with AWS EMR for distributed data processing.
• Develop and support cloud-based data solutions using AWS services.
• Perform data cleansing, transformation, validation, and quality checks.
• Process large volumes of telecom data such as customer, network, usage, billing, and operational data.
• Troubleshoot data pipeline failures and improve performance and reliability.
• Collaborate with data architects, analysts, developers, and business teams.
• Participate in production support, debugging, and performance tuning.

Required Qualifications:

• Strong experience in Data Engineering and ETL/ELT development.
• Strong SQL skills, including complex queries, joins, CTEs, window functions, and performance tuning.
• Hands-on experience with Apache Spark / PySpark.
• Strong experience with AWS EMR and distributed data processing.
• Good understanding of AWS cloud data services.
• Experience working with large datasets and high-volume data processing.
• Strong troubleshooting and problem-solving skills.

Preferred Telecom Experience:

• Experience working with Telecom/Communications domain data.
• Knowledge of network, customer, usage, billing, CDR, and service data.
• Experience with telecom data warehouses, data lakes, or analytics platforms.