Senior AWS Data Engineer - ETL, Spark & Redshift

NTT DATA, Inc.; Memphis (TN); Hybrid; USD 98,000 - 163,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) with company match

Paid time off

Flexible spending or HSA

AD&D and life insurance

Job summary

NTT DATA is seeking a highly experienced data engineering leader to design, develop, and maintain scalable data pipelines using Spark (Scala/Python), AWS Glue and Lambda. You will optimize Redshift SQL/PLSQL, support ETL/ELT processes, and ensure data governance and privacy across multiple data sources.

With 12+ years in data warehouses/big data and 5+ years in a lead role, you will collaborate with business and technical teams to deliver enterprise data solutions and drive customer insights

Qualifications

• 12+ years of experience in Data Warehouse / Big Data ecosystems.
• 5+ years in a lead / SME role.
• 5+ years with AWS architecture and data engineering (S3, EC2, Redshift RA3/Serverless, S3 Hive, AWS Glue, Lambda, Kafka, Airflow, Iceberg).
• 3+ years with Spark (Scala/Python).
• 5+ years with SQL/PLSQL, MySQL.
• Strong understanding of ETL/ELT frameworks, distributed data processing, data governance and security.

Responsibilities

• Design, build, and maintain scalable data pipelines using Spark, AWS Glue, and Lambda.
• Develop and optimize Redshift SQL/PLSQL code, stored procedures, and data-processing frameworks.
• Perform query tuning and data-sharing implementations across AWS platforms (S3, Hive, Iceberg, Redshift).
• Integrate multiple data sources to support reporting, analytics, and customer engagement initiatives.
• Lead cross-team collaboration and contribute to data governance and privacy initiatives.

Skills

Spark (Scala/Python)

AWS Glue

AWS Lambda

Shell scripting

Redshift SQL/PLSQL

MySQL

Data Modeling

Query Optimization

ETL/ELT

Data governance

Education

Bachelor's degree in CS/IT

Tools

Apache Iceberg

Kafka

Airflow

Redshift

Job description

NTT DATA is seeking a highly experienced data engineering leader to design, develop, and maintain scalable data pipelines using Spark (Scala/Python), AWS Glue and Lambda. You will optimize Redshift SQL/PLSQL, support ETL/ELT processes, and ensure data governance and privacy across multiple data sources.

With 12+ years in data warehouses/big data and 5+ years in a lead role, you will collaborate with business and technical teams to deliver enterprise data solutions and drive customer insights