Senior Data Platform Engineer

We are seeking an experienced technical leader to spearhead the development and implementation of a scalable, multitenant modern data platform.

This role requires hands-on experience in managing Snowflake environments, designing data pipelines, 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.

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

Required Competencies, Experience, and Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related technical field.
• 6+ years of experience in data engineering or platform delivery, including 3+ years of hands-on Snowflake experience in production environments.
• Proven expertise in building and managing multitenant data platforms, including schema isolation, RBAC, and masking policies.
• Solid knowledge of CI/CD practices for data projects, with experience guiding pipeline implementations using tools like GitHub Actions.
• Hands-on experience with dbt, SQL, and metadata-driven pipeline design for large-scale ingestion and transformation workloads.
• Strong understanding of AWS cloud services relevant to data platforms (e.g., S3, IAM, Lambda, CloudWatch, Secrets Manager).
• Experience optimizing Snowflake performance, including warehouse sizing, caching, and cost control strategies.
• Familiarity with setting up observability frameworks, monitoring tools, and data quality checks across complex pipeline ecosystems.
• Proficient in infrastructure-as-code (IaC) concepts and managing configuration/versioning across environments.
• Awareness of data governance principles, including lineage, PII handling, and tenant-specific metadata tagging.