Support spans implementation, system and data architecture, CI/CD-aware execution, and practical collaboration with platform and deployment teams.
ETL Modernization
Upgrade fragile legacy pipelines into scalable, testable, cloud-native workflows.
Deliverables
- Current-state architecture review
- Target-state ingestion blueprint
- Migration plan with risk controls
- Pilot pipeline implementation
Ideal For
- Teams migrating from on-prem
- Data teams with frequent production incidents
Lakehouse Platform Design
Design medallion-based data platforms with governance, performance, and maintainability in mind.
Deliverables
- Zone and table strategy
- Orchestration model
- Quality and observability standards
- Cost/performance optimization checklist
Ideal For
- Growing analytics organizations
- Enterprise data platform programs
Technical Delivery Leadership
Hands-on leadership for teams needing architecture direction, deployment alignment, code quality uplift, and unblock support.
Deliverables
- Architecture decision facilitation
- CI/CD and release workflow alignment with platform teams
- Docker, Kubernetes, Jenkins, ArgoCD, and Azure DevOps collaboration
- PR/process quality standards
- Stakeholder technical communication
- Mentorship for junior engineers
Ideal For
- Projects under schedule pressure
- Cross-functional delivery squads
Quantexa Implementation Support
Support teams implementing Quantexa after licensing, with emphasis on data readiness, workflow quality, and practical delivery support.
Deliverables
- Source-data readiness review for Quantexa workflows
- Implementation support for insurance and banking use cases
- Scala/Spark delivery contribution within Quantexa projects
- Stakeholder communication around workflow and data quality behavior
Ideal For
- Teams that already own Quantexa licenses
- Programs needing delivery support rather than custom ER engine development