Data Engineer: Lakehouse Migrations to AWS

NTT Data Americas, Inc.; Dallas (TX); On-site; USD 90,000 - 106,000; Full time

Job summary

NTT DATA is seeking a Data Engineer to join our Seattle-based migration team. You will migrate data from on-prem DataLake to AWS Lakehouse, refactor existing pipelines, and ensure data integrity across source and target platforms.

Responsibilities include translating legacy SQL/Spark logic to Snowflake/Iceberg, validating data with stakeholders, and optimizing pipelines for performance and scalability. Requires 3+ years in data engineering and experience with Spark, Snowflake, and CI/CD.

Qualifications

• Minimum 3+ years of software development/data engineering experience.
• Experience with SQL development, analysis, and performance optimization.
• 3+ years programming in Python and/or Java for data processing or integration.
• Experience building or supporting ETL/ELT data pipelines and data migrations.

Responsibilities

• Migrate data from on-prem DataLake to AWS Lakehouse platforms.
• Refactor and migrate data pipelines and scheduling jobs.
• Ensure data integrity and validation during migrations.
• Collaborate with cross-functional teams and stakeholders to sign off on migrations.
• Troubleshoot and optimize data pipelines for performance and scale.
• Apply data engineering concepts including SCD Type 2, schema evolution, partitioning.
• Work with JSON, Avro, Parquet data formats.
• Follow SDLC/CI–CD practices and use version control.

Skills

SQL

Python/Java

ETL/ELT

Apache Spark

Snowflake

Apache Iceberg

Kafka

Hadoop

CI/CD

SDLC

Kubernetes

Education

Bachelor's degree in Computer Science or related field

Tools

Snowflake

Apache Iceberg

Job description

NTT DATA is seeking a Data Engineer to join our Seattle-based migration team. You will migrate data from on-prem DataLake to AWS Lakehouse, refactor existing pipelines, and ensure data integrity across source and target platforms.

Responsibilities include translating legacy SQL/Spark logic to Snowflake/Iceberg, validating data with stakeholders, and optimizing pipelines for performance and scalability. Requires 3+ years in data engineering and experience with Spark, Snowflake, and CI/CD.