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Kunai
via Greenhouse
Senior Cloud Data Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 96d ago
The date the source published, not the day we noticed it (2026-06-10). Last seen at its source 1h ago.
Is it remote?
Remote - United States
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $161k–210k/yr
Middle 50% of 741 listings that do state pay — Engineering · Senior · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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greenhouse employer's own board first seen 11d ago · last seen 1h ago
The listing
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 (Associate or Professional)
- AWS Certified Data Analytics Specialty or Database Specialty
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- Google Professional Cloud Architect or Cloud Data Engineer
Our success over the past 20 years is rooted in our exceptional team, which thrives in a culture of collaboration, creativity, and continuous learning.
We are proud to offer our employees a range of benefits, including competitive compensation, professional development opportunities, and flexible work arrangements, all designed to help them thrive. As we continue to expand, we remain committed to cultivating an environment where people feel valued, have a voice, and are given the tools to grow—both personally and professionally—while pushing the boundaries of innovation in the fintech industry.
Minimum Degree Required:
- Bachelor’s Degree, in lieu of a degree, demonstrating in addition to the minimum years of experience required for the role, three years of specialized training and/or progressively responsible work experience in technology for each missing year of college is required