Data Engineer (Cloud AWS), hibrido

Quantiphi is an award-winning, AI-First global digital engineering company that helps the world’s leading Fortune 1000 organizations transform bold ideas into measurable business impact. We go beyond building innovative AI technologies—we solve the problems that matter most to our clients. Headquartered in Boston, with more than 4,000 professionals worldwide, we partner with global enterprises to deliver large-scale digital, cloud, and AI-driven transformation. #We are an Elite and Premier partner to Google Cloud, AWS, NVIDIA, Snowflake, and other leading technology platforms, and our work has been recognized across the industry, including: ~3 AWS AI/ML Partner of the Year awards ~Quantiphi delivers First-in-class AI solutions across Life Sciences, Healthcare, Banking, Financial Services, CPG, Manufacturing, Energy, High-Tech, Telecommunications, etc., powered by cutting-edge Generative AI and Agentic AI accelerators. Website or LinkedIn Page Role: Cloud Data Architect (AWS) Full Time Location: Remote (UK) We are seeking a highly skilled AWS Data Migration & Data Engineering Consultant to lead end-to-end data migration initiatives across on-prem, cloud, and multi-cloud environments into AWS. This role focuses on defining and executing data migration strategies, including assessment, wave planning, migration execution, and post-migration stabilization, while ensuring data integrity, minimal downtime, and alignment with business SLAs. The ideal candidate brings strong experience in cross-platform database migrations (Oracle, SQL Server, MySQL, or cloud-native systems) combined with deep expertise in AWS data engineering services and modern data pipeline development. Lead end to end database migrations to AWS from diverse sources, including on-premises systems (e.g., Oracle, SQL Server, MySQL) and other cloud platforms (e.g., Lead end-to-end data migration strategy and execution, including assessment, dependency mapping, and wave planning. Design and implement migration frameworks using AWS DMS, SCT, Glue, and Redshift. Define and execute data validation, reconciliation, and cutover strategies ensuring zero/low data loss. Design and optimize ETL/data pipelines using AWS Glue, PySpark, or EMR. Architect and implement scalable, secure, and highly available data platforms on AWS. Optimize performance of source and target systems pre- and post-migration. Manage and govern S3-based data lakes and metadata using Glue Data Catalog. Implement monitoring, rollback, and failure recovery mechanisms. 8+ years of experience in database migration and data engineering. ~ Proven experience in cross-platform data migrations (on-prem to cloud or cloud to cloud). ~ Experience designing and implementing data validation and reconciliation frameworks. ~ Strong experience in ETL/data pipeline development (Glue, PySpark, EMR, or equivalent). ~ Deep proficiency in SQL and data modeling concepts. ~ Experience working with S3-based data lakes and Glue Data Catalog. ~ Hands-on experience with performance tuning, schema design, and query optimization. ~ Proficiency in Python/PySpark and scripting (Shell/Python). ~ Experience with Oracle, SQL Server, MySQL, PostgreSQL, or cloud-native databases. AWS DMS (Database Migration Service). AWS SCT (Schema Conversion Tool). AWS Glue (ETL & data integration). Amazon Redshift (data warehousing). Database Administration (DBA) expertise, including backup & recovery strategies, HA/DR design, database patching and upgrades, lifecycle management, capacity planning, performance monitoring, and security hardening. Experience with Lake Formation and data governance frameworks. Familiarity with Data Mesh and cross-account data sharing architectures. Experience with CI/CD for data pipelines (CodePipeline, Jenkins, etc.). AWS Certifications (Solutions Architect / Data Engineer). Join one of the world’s fastest-growing AI-first digital engineering companies and make a real impact at scale. Stay ahead of the curve by gaining hands-on experience with cutting-edge AI, ML, data, and cloud technologies while continuously upskilling.