Data Engineer (DataLake to AWS)

NTT DATA, Inc.; Seattle (WA); On-site; USD 90,000 - 106,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401k with company match

Paid time off

Employee assistance

Job summary

NTT DATA, Inc. in Seattle, WA seeks a Data Engineer to migrate and modernize data pipelines from on-prem DataLake to AWS Lakehouse. You will refactor ETL/ELT workflows, optimize transfers, and support validation with business teams across the migration lifecycle.

The role requires 3+ years in data engineering, expertise in SQL, Python/Java, Spark, Snowflake, and Iceberg, and familiarity with SDLC/CI/CD in a distributed environment. Onsite in Seattle, 9+ month engagement.

Qualifications

• 3+ years in software/data engineering with ETL/ELT pipelines.
• 3+ years SQL development and performance optimization.
• 3+ years Python or Java for data processing.
• Experience with Spark and Snowflake/Iceberg.

Responsibilities

• Perform end-to-end datastore migrations from on-prem DataLake to AWS Lakehouse.
• Refactor and migrate data pipelines and job scheduling.
• Execute large-scale data transfers with integrity and consistency.
• Translate legacy SQL/Spark logic for Snowflake and Iceberg.
• Collaborate with stakeholders to validate migrations.

Skills

SQL

Python/Java

ETL/ELT

Apache Spark

Snowflake

Iceberg

Kubernetes

CI/CD

Data Lake

Data Migration

Education

Bachelor's degree

Tools

Kafka

Hadoop

Job description

Data Engineer (DataLake to AWS)

26-02007 100% Onsite in Seattle, WA 9+ Months Duration Temp W2 or C2C

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,

NTT DATA's Client is seeking a Data Engineer to join our team in Seattle, Washington (US-WA), United States (US).

Job Description

• Perform end-to-end datastore migrations from on-premises DataLake environments to AWS-hosted Lakehouse platforms as part of the migration factory team.
• Refactor and migrate existing data pipelines, including data extraction logic, transformation processes, and job scheduling.
• Execute large-scale data transfers while ensuring data integrity, completeness, reliability, and consistency between source and target platforms.
• Translate and modernize legacy SQL and Apache Spark-based processing logic for Snowflake and Apache Iceberg environments.
• Analyze existing data usage patterns, business requirements, and downstream consumption to support the development and delivery of reusable data products.
• Design and build data reconciliation and validation frameworks to verify data accuracy during and after migration.
• Collaborate with business stakeholders, application teams, data owners, and technical teams to perform validation and obtain migration sign-off.
• Act as a technical liaison between migration, data engineering, application, infrastructure, and business teams throughout the migration lifecycle.
• Troubleshoot data pipeline, data transformation, performance, and migration-related issues and implement appropriate technical solutions.
• Optimize data pipelines and processing workloads to improve performance, scalability, and operational efficiency.
• Apply core data engineering concepts including Slowly Changing Dimensions (SCD Type 2), schema evolution, partitioning, clustering, normalization and denormalization, natural and surrogate keys, and data quality controls.
• Work with structured and semi-structured data formats including JSON, Avro, and Parquet.
• Follow established Software Development Life Cycle (SDLC), source-control, testing, deployment, and Continuous Integration/Continuous Deployment (CI/CD) practices.
• Adapt to new data technologies, migration tools, engineering standards, and workflows as required by the program.
• Collaborate effectively with geographically distributed and global delivery teams.

Basic Qualifications

• Minimum 3+ years of hands‑on software development and/or data engineering experience, including coding, development, troubleshooting, and implementation of data‑related solutions.
• Minimum 3+ years of experience working with SQL, including development, analysis, query troubleshooting, and performance optimization.
• Minimum 3+ years of hands‑on programming experience using Python and/or Java for data processing, application development, automation, or integration.
• Minimum 3+ years of experience developing or supporting ETL/ELT data pipelines, including data extraction, transformation, loading, and pipeline troubleshooting.
• Experience developing or supporting distributed data‑processing solutions using Apache Spark.
• Experience working with data engineering concepts including SCD Type 2, schema evolution, partitioning, clustering, normalization versus denormalization, natural versus surrogate keys, and data quality frameworks.
• Experience working with one or more data and integration technologies including Kafka, ANSI SQL, FTP, Apache Spark, Hadoop, Snowflake, Apache Iceberg, and Sybase IQ.
• Experience working with structured and semi-structured data formats including JSON, Avro, and Parquet.
• Experience working within established SDLC and CI/CD processes, including source control, testing, deployment, and release practices.
• Familiarity with containerized application environments and Kubernetes.
• Demonstrated ability to troubleshoot technical issues, communicate effectively with stakeholders, collaborate across global teams, and take ownership of assigned deliverables.

Travel

• No specific travel requirement has been identified for this position.

Degree

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field, or equivalent work experience.

Nice to Have

• Experience performing large‑scale data platform or datastore migration initiatives.
• Experience migrating data workloads from on-premises environments to cloud-based platforms, particularly AWS.
• Experience working with Lakehouse architectures.
• Experience with Snowflake and Apache Iceberg-based data platforms.
• Experience working within the financial services industry.
• Experience supporting complex migration programs involving multiple business, technology, and global delivery teams.

About NTT DATA

Where required by law, NTT DATA provides a reasonable range of compensation for specific roles. The starting hourly range for this remote role is $65 to $77. This range reflects the minimum and maximum target compensation for the position across all US locations. Actual compensation will depend on several factors, including the candidate's actual work location, relevant experience, technical skills, and other qualifications. This position may also be eligible for incentive compensation based on individual and/or company performance.

This position is eligible for company benefits that will depend on the nature of the role offered.

• medical insurance
• dental insurance
• vision insurance
• flexible spending or health savings account
• life insurance
• AD&D insurance
• short‑term disability coverage
• long‑term disability coverage
• paid time off
• employee assistance
• participation in a 401k program with company match
• additional voluntary or legally required benefits

NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at us.nttdata.com

NTT DATA endeavors to make https://us.nttdata.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at https://us.nttdata.com/en/contact-us. This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.