AWS ETL Data Engineer - HYBRID

Req ID: 382980 

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a AWS ETL Data Engineer - HYBRID to join our team in Memphis, Tennessee (US-TN), United States (US).

We are seeking an experienced technical resource who could design, develop, support, and enhance enterprise data platforms while ensuring compliance with privacy and data governance requirements. The role combines data engineering, systems integration, analytics, solution design, and operational support.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Spark (Scala/Python), AWS Glue, AWS Lambda, and Shell scripting.
• Build and support ETL/ELT processes across AWS platforms, including S3, Hive, Apache Iceberg, and Amazon Redshift.
• Develop and maintain Redshift SQL/PLSQL code, stored procedures, and data-processing frameworks.
• Perform query tuning, performance optimization, and data-sharing implementations.
• Support ingestion and processing of structured and semi-structured data formats including JSON, CSV, XML, ORC, Parquet, and Avro.
• Design, enhance, and support  solutions that provide a unified view of customer data across systems.
• Integrate multiple data sources, applications, and business processes to support reporting, analytics, and customer engagement initiatives.
• Collaborate with business and technical teams to define and implement scalable data solutions.
• Manage and support Data Subject Requests (DSRs), including customer data erasure requests.
• Work closely with the DPO team to ensure compliance with privacy regulations and internal policies.
• Maintain and support the MicroStrategy Privacy Compliance module. (Very infrequent once in year or 2 years)
• Contribute to data governance initiatives that improve data quality, consistency, and compliance.
• Analyze and troubleshoot complex data issues using Redshift SQL, MySQL, Python/PySpark, Shell scripting, and Excel.
• Investigate data mismatches, reporting issues, and business data anomalies.
• Support business analysis related to customer tiers, loyalty programs, and email marketability.
• Provide production support and root-cause analysis for critical data platform issues.

 

Technical Leadership & Collaboration

• Participate in Customer 360, Privacy, Data Governance, and Phaedon initiatives.
• Conduct code reviews and design reviews.
• Provide cross-team technical support and problem resolution.
• Research, design, and develop next-generation data capabilities and products.
• Act as a subject matter expert for customer data platforms.

Primary Technologies

• AWS: S3, EC2, Redshift (RA3/Serverless), S3 Tables, S3 Hive, AWS Glue, Lambda (Python), Kafka, Airflow, Apache Iceberg
• Spark (Scala/Python)
• Redshift SQL/PLSQL, MySQL
• Data Modeling and Query Optimization 

Key Strengths

• Strong ownership and accountability
• Strong AWS Data Engineering stack awareness
• Ability to bridge business and technical teams
• Expertise across engineering, analytics, compliance, architecture, and operational support
• Adaptability and willingness to take on diverse data-related challenges

Minimum Requirements:

• 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, including S3, EC2, Redshift (RA3/Serverless), S3 Tables, S3 Hive, AWS Glue, Lambda (Python), Kafka, Airflow, Apache Iceberg
• 3+ years with Spark (Scala/Python)
• 5+ years with SQL/PLSQL, MySQL
• 5+ years strong understanding of:

• Data architecture & dimensional modeling
• ETL/ELT frameworks<