Data Platform Architect Lead

2 weeks ago

Tiruchi, Tamil Nadu, India beBeeCloud Full time US$ 1,20,000 - US$ 1,60,000
Job Description

We are seeking a highly skilled and proactive professional to lead the implementation and operational excellence of a scalable, multitenant modern data platform.

This role requires hands-on experience in managing cloud services, supporting data pipeline orchestration, enforcing platform-level standards, and ensuring observability, performance, and security across environments.

You will collaborate with architects, engineers, and DevOps teams to operationalize the platform's design and drive its long-term stability and scalability in a cloud-native ecosystem.

Key Responsibilities
  1. Lead the technical implementation and stability of the multitenant data platform across dev, QA, and prod environments
  2. Design and manage schema isolation, role-based access control (RBAC), masking policies, and cost-optimized architecture for multiple nonprofit tenants
  3. Implement and maintain CI/CD pipelines for dbt, metadata-driven ingestion processes using GitHub Actions or similar tools
  4. Develop and maintain automation accelerators for data ingestion, schema validation, error handling, and onboarding new clients at scale
  5. Collaborate with architects and data engineers to ensure seamless integration with source CRMs, ByteSpree connectors, and downstream BI/reporting layers
  6. Monitor and optimize performance of workloads (e.g., query tuning, warehouse sizing, caching strategy) to ensure reliability and scalability
  7. Establish and maintain observability and monitoring practices across data pipelines, ingestion jobs, and platform components (e.g., error tracking, data freshness, job status dashboards)
  8. Manage infrastructure-as-code (IaC), configuration templates, and version control practices across the data stack
  9. Ensure robust data validation, quality checks, and observability mechanisms are in place across all platform services
  10. Support incident response, pipeline failures, and technical escalations in production, coordinating across engineering and client teams.
  11. Contribute to data governance compliance by implementing platform-level policies for PII, lineage tracking, and tenant-specific metadata tagging

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