AWS ETL Data Engineer - HYBRID

About the role

NTT DATA seeks to hire exceptional, innovative, and passionate individuals who want to grow with us. We are currently looking for an AWS ETL Data Engineer - HYBRID to join our team in Memphis, Tennessee (US-TN), United States (US).

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.
• 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.
• 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.

Requirements

• 12+ years of experience in Data Warehouse / Big Data ecosystems.
• 5+ years in a lead / SME role 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, Distributed data processing, Cloud data platforms, Data governance and security.

Qualifications

• 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.

Skills

• Experience managing large-scale enterprise data environments.
• Proven track record of delivering complex data programs.
• Excellent communication and stakeholder management abilities.
• Experience in large enterprise or global delivery environments.
• Exposure to data modernization and cloud transformation programs.
• Certifications in cloud platforms or data engineering.
• Experience in regulated industries (Hospitality, Finance, Healthcare, Telecom, etc.).

Benefits

This position is eligible for company benefits including medical, dental, and vision insurance with an employer contribution, flexible spending or health savings account, life and AD&D insurance, short and long term disability coverage, paid time off, employee assistance, participation in a 401k program with company match, and additional voluntary or legally-required benefits.

Pay

The starting pay range for this role is $97,725 – 162,875. Actual compensation will depend on a number of factors, including the candidate’s relevant experience, technical skills, and other qualifications.