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Data Migration Engineer

Job in London, Greater London, W1B, England, UK
Listing for: NTT DATA
Full Time position
Listed on 2026-09-09
Job specializations:
  • IT/Tech
    Data Engineering, AWS
Job Description & How to Apply Below
The team you'll be working with:

We are seeking a detail-oriented and capable Data Migration Engineer to join our Data & AI practice. The successful candidate will bring solid experience in data migration, ETL/ELT pipeline development, and cloud-based data platforms, with a focus on AWS Data Lakehouse environments.

This role is key to supporting the design, build, and validation of data migration pipelines, enabling the successful transition of data from legacy systems to modern cloud platforms. You will contribute to ensuring data quality, integrity, and performance, particularly through structured testing and validation activities.

You will work closely with architects, senior engineers, and analysts to deliver scalable and reliable migration solutions, using technologies such as AWS Glue, Apache Iceberg, Python/PySpark, SQL, and YAML configurations. You should be comfortable working in a collaborative, delivery-focused environment and have a strong interest in data migration, cloud technologies, and modern data engineering practices.

What you'll be doing:

Client Engagement & Delivery Support delivery within data migration programmes, contributing to key work streams

Collaborate with architects, engineers, and stakeholders to implement migration solutions

Assist in planning and executing data migration tasks and deliverables

Data Migration Engineering Build and maintain data migration pipelines from legacy data warehouses to AWS-based platforms

Develop ETL/ELT pipelines using:

AWS Glue Python / PySparkSQLYAML configurations

Support execution of bulk data migrations and incremental/delta loads

Assist with pipeline repointing and migration to cloud environments

Data Pipeline Testing & Validation (Core Focus)
Test ETL/ELT data pipelines on AWS services, including AWS Glue and Apache Iceberg Support validation of data pipeline migrations to AWS Data Lakehouse architectures

Test pipelines using:

Python/PySpark transformations SQL-based validation logicYAML-driven configurations

Execute and validate:

Initial bulk data loads

Incremental/delta data processing

Write and run SQL queries to validate:

Data completeness

Data accuracy

Transformation outputs

Support development of test scripts and validation checksAWS Data Platforms & Lakehouse Work with AWS services including:

AWS GlueS3-based data lakes

Support implementation of Data Lakehouse architectures, including Apache Iceberg Contribute to improving pipeline performance and reliability

Data Transformation & Support Apply transformation logic based on defined data mapping rules

Support preparation of data for target-state models

Assist in ensuring consistency between source and target datasets

Collaboration & Best Practices Work collaboratively with:

Solution Architects Data Engineers Data Migration Architects Analysts and QA teams

Follow established engineering standards and best practices

Contribute to documentation and reusable components

Quality, Governance & Security Support maintenance of data quality and integrity during migration

Follow secure data handling practices

Assist with compliance requirements, including:

GDPRPublic sector data standards (where applicable)
Contribute to testing, validation, and audit activities

What experience you'll bring:

Experience in data engineering or data migration delivery

Strong focus on testing, validation, and data quality assurance

Ability to work across data pipelines and transformation workflows

Good analytical and problem-solving skills

Effective communication and teamwork skills

Willingness to learn and develop in data migration and cloud technologies

Technical Expertise Hands-on experience with:

AWS cloud services, especially AWS Glue Python / PySparkSQL querying and validationYAML configuration (desirable)
Experience testing or supporting:

ETL/ELT pipelines

Data migration processes

Familiarity with:

Data lake / Lakehouse concepts (e.g., Apache Iceberg)
Distributed processing frameworks (e.g., Spark)
Basic understanding of:

ETL vs ELT approaches

Cloud-based data architectures

Exposure to version control and CI/CD tools desirable

Who we are:

We’re a business with a global reach that empowers local teams, and we undertake hugely exciting work that is…
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