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Senior Cloud Data Engineer

Kunai
CompanyKunai
CategoryEngineering
LocationRemote - United States
RemoteRemote
EmploymentNot stated
LevelSenior
SalaryNot stated by the employer
Posted10 Jun 2026
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
Kunai builds full-stack technology solutions for banks, credit and payment networks, infrastructure providers, and their customers. Together, we are changing the world’s relationship with financial services. At Kunai, we help our clients modernize, capitalize on emerging trends, and evolve their business for the coming decades by remaining tech-agnostic and human-centered. This is a chance to work at the center of a complex and consequential cloud transformation for a major financial services org. We are looking for sharp, delivery-focused data consultants to lead the migration of a large data platform from Google Cloud Platform to AWS. You will not be reviewing architecture diagrams from the sidelines; you will be building the pipelines, designing the schemas, and making the hard calls that keep petabytes of critical financial data moving accurately and on schedule.   If you thrive in technically demanding environments, love solving gnarly data problems, and want your fingerprints on an enterprise-scale transformation, this engagement is for you.     What You Will Do   Own end-to-end data migration execution: Drive the full OLAP/OLTP migration from GCP to AWS: data mapping, schema conversion, and hands-on lift-and-shift execution.   Build rock-solid synchronization pipelines: Design and implement data sync pipelines with tight SLAs for latency, consistency, and error recovery. Zero ambiguity on failure modes.   Bring the target architecture to life: Implement the AWS data architecture end to end, including driver personalization engines and production-grade dashboarding solutions.   Migrate historical and time-series data at scale: Execute large-volume historical data migrations with rigorous integrity checks and minimal disruption to live operations.   Build observability from the ground up: Create monitoring, alerting, and reconciliation frameworks that give the team real-time confidence in cross-cloud data fidelity.   Elevate the team around you: Share your expertise freely. Mentor peers, unblock blockers, and raise the technical floor of the whole engagement.   Partner closely with the client: Work shoulder-to-shoulder with stakeholders to nail data governance, access patterns, and analytics requirements.     What You Bring   Data Migration   BigQuery to Redshift, Cloud SQL to Aurora/RDS: you have done this before and have the scars to prove it   Data mapping, schema conversion, and ETL/ELT pipeline design at enterprise scale   OLAP and OLTP Systems   Dimensional modeling: star and snowflake schemas, done right   Transactional database optimization and time-series data migration   Data Synchronization   CDC (Change Data Capture), real-time replication, latency tuning   Strong opinions on eventual vs. strong consistency, and when each applies   Battle-tested error handling and retry strategies   AWS Data Services   Redshift, Aurora PostgreSQL, DMS, Glue, Kinesis, MSK (Kafka), Lambda, S3, Lake Formation   Analytics and Personalization   Amazon QuickSight, Grafana, dashboarding frameworks, driver personalization engines   GCP   BigQuery, Cloud Spanner, Dataflow, Pub/Sub, Cloud SQL: you know the terrain you are leaving   Infrastructure as Code and CI/CD   Terraform, CloudFormation, and automated CI/CD for data pipelines     Certifications   Cloud certifications are a plus but are not required. Any of the following, or equivalent credentials from a major cloud provider, are valued:   AWS Certified Solutions Architect (Associat
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Senior Cloud Data Engineer — Kunai · Job Opportunities API