You will own foundational data assets end to end, from ingestion and transformation through modeling, validation, delivery, monitoring, security, and cost optimization. This is a production-focused role where engineers own live systems, not only task-level deliverables.
What will you do:
Build and maintain production-grade Snowflake pipelines using incremental loading, CDC patterns, backfills, reconciliation, and idempotent processing.
Own data flows from Salesforce and other source systems into Snowflake, including ingestion, transformation, validation, monitoring, and delivery.
Model data into analytics-ready datasets, dimensional models, facts, dimensions, star schemas, and reusable business entities.
Develop core Snowflake objects.
Create governed, AI-ready semantic models and curated datasets for Cortex Analyst, Cortex Search, BI tools, and enterprise AI integrations
Apply Snowflake FinOps practices for cost-aware design.
Apply security and governance best practices, including RBAC, least privilege, masking policies, row access policies, secure views, auditability, and safe handling of sensitive data.
Partner with stakeholders to define certified metrics, source-to-target mappings, trusted data contracts, and reusable analytical entities.
Requirements:
5+ years of hands-on experience building production data solutions for SaaS organizations on Snowflake as a Data Engineer, BI Developer, Analytics Engineer, or similar role.
Strong experience with Snowflake objects and capabilities, including warehouses, databases, roles, schemas, views, stored procedures, tasks, streams, and performance tuning.
Experience building reliable ELT or ETL pipelines using incremental loads, CDC, backfills, reconciliation, and idempotent processing.
Strong dimensional modeling and data warehousing foundations, including facts, dimensions, star schemas, marts, and reusable business entities.
Salesforce data experience, including core objects, relationships, API limitations, and Salesforce-to-warehouse pipelines.
Hands-on experience with Snowflake Cortex capabilities such as Cortex Analyst, Cortex Search, Cortex LLM functions, and governed AI data access patterns.
Experience building AI-ready semantic models and curated datasets for governed analytics, BI, and enterprise AI use cases.
Understanding of secure enterprise AI integration patterns, including governed structured data access and MCP-based integrations.
Strong knowledge of data governance, privacy, security, RBAC, masking policies, row access policies, secure views, and compliance-aware data handling.
Proven Snowflake FinOps experience, including credit monitoring, warehouse sizing, workload optimization, storage awareness, and query cost reduction.
Strong system analysis, requirements gathering, source-to-target mapping, lineage, impact analysis, and stakeholder communication skills.
Nice to have:
Python for data processing, automation, testing, or operational tooling.
AWS cloud data experience.
Experience with Snowpark or Snowpark ML.
Experience with BI tools such as Sisense, Tableau, or Power BI.
Experience with data observability, orchestration, CI/CD, or automated testing for data pipelines.
