高级云数据工程师
Senior Cloud Data Engineer
Kunai 为银行、信用和支付网络、基础设施提供商及其客户构建全栈技术解决方案。我们正在改变世界与金融服务的关系。在 Kunai,我们通过保持技术中立和以用户为中心,帮助客户现代化,把握新兴趋势,并为其未来几十年的发展演变提供支持。
这是一个在一家主要金融服务机构的复杂且具有深远影响的云转型中心工作的机会。我们正在寻找思维敏捷、注重交付的数据顾问,领导将大型数据平台从 Google Cloud Platform 迁移到 AWS。你不会只是从旁观察架构图;你将构建数据管道,设计数据模式,并做出确保数 PB 的关键金融数据准确且按时流动的关键决策。
如果你在技术要求高的环境中茁壮成长,喜欢解决复杂的数据问题,并希望在企业级转型中留下自己的印记,那么这个项目适合你。
你将负责的工作
- 负责端到端的数据迁移执行:推动从 GCP 到 AWS 的完整 OLAP/OLTP 迁移:数据映射、模式转换以及实际的迁移执行。
- 构建稳固的数据同步管道:设计并实现具有严格 SLA 的数据同步管道,确保延迟、一致性和错误恢复。对失败模式零模糊。
- 实现目标架构:从头到尾实现 AWS 数据架构,包括驱动个性化引擎和生产级仪表盘解决方案。
- 大规模迁移历史和时序数据:执行大规模历史数据迁移,进行严格的完整性检查,并最大程度减少对实时操作的干扰。
- 从零开始构建可观测性:创建监控、警报和对账框架,使团队能够实时确保存在跨云数据的一致性。
- 提升周围团队的能力:自由分享你的专业知识。指导同事,解除障碍,提升整个项目的整体技术水平。
- 与客户紧密合作:与利益相关者肩并肩工作,确保数据治理、访问模式和分析需求得到落实。
你带来的能力
数据迁移
- 从 BigQuery 迁移到 Redshift,Cloud SQL 迁移到 Aurora/RDS:你之前做过,并有经验可以证明
- 在企业规模上进行数据映射、模式转换和 ETL/ELT 管道设计
查看英文原文
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