3 months ago
Responsibilities
- Own end-to-end OLAP/OLTP data migration execution from GCP to AWS, including data mapping, schema conversion, and lift-and-shift execution.
- Design and implement data synchronization pipelines with strict latency, consistency, and error-recovery requirements.
- Implement AWS data architecture, including personalization engines and production dashboarding solutions.
- Execute large-volume historical and time-series data migrations with integrity checks and minimal operational disruption.
- Build monitoring, alerting, and reconciliation frameworks for cross-cloud data fidelity.
- Mentor peers, remove technical blockers, and raise the technical capability of the engagement team.
- Partner with client stakeholders on data governance, access patterns, and analytics requirements.
Requirements
- Hands-on experience migrating data between BigQuery and Redshift and between Cloud SQL and Aurora/RDS.
- Experience with enterprise-scale data mapping, schema conversion, and ETL/ELT pipeline design.
- Knowledge of OLAP and OLTP systems, dimensional modeling, star and snowflake schemas, transactional database optimization, and time-series data migration.
- Experience with change data capture, real-time replication, latency tuning, consistency models, error handling, and retry strategies.
- Experience with AWS data services including Redshift, Aurora PostgreSQL, DMS, Glue, Kinesis, MSK (Kafka), Lambda, S3, and Lake Formation.
- Experience with analytics and personalization solutions including Amazon QuickSight, Grafana, dashboarding frameworks, and driver personalization engines.
- Experience with GCP services including BigQuery, Cloud Spanner, Dataflow, Pub/Sub, and Cloud SQL.
- Experience with Terraform, CloudFormation, and automated CI/CD for data pipelines.
- Cloud certifications are valued but not required, including AWS Certified Solutions Architect, AWS Certified Data Analytics Specialty, AWS Certified Database Specialty, Google Professional Cloud Architect, or Google Cloud Data Engineer certifications.
- Bachelor’s degree required, with equivalent specialized training and progressively responsible technology experience permitted in lieu of missing college years.
Benefits
- Competitive compensation.
- Professional development opportunities.
- Flexible work arrangements.
Tech Stack
Categories
Data EngineeringDevOps
About Kunai
Kunai is a digital product development and engineering consultancy focused on financial services, building full-stack systems for banks, payment networks, and fintechs. Its teams deliver product development, AI and automation, cloud, and data engineering, partnering from MVP through rollout. Founded in 2015 and headquartered in San Ramon, California, Kunai was acquired by PwC and operates within the PwC network serving large U.S. banks and global card networks.