Senior BI Data Engineer

Who are we?

Checkmarx is the leader in application security and ensures that enterprises worldwide can secure their application development from code to cloud. Our consolidated platform and services address the needs of enterprises by improving security and reducing TCO, while simultaneously building trust between AppSec, developers, and CISOs. At Checkmarx, we believe it’s not just about finding risk, but remediating it across the entire application footprint and software supply chain with one seamless process for all relevant stakeholders.

We are honored to serve more than 1,800 customers, which includes 40 percent of all Fortune 100 companies including Siemens, Airbus, SalesForce, Stellantis, Adidas, Wal-Mart and Sanofi.

What we are looking for:

Checkmarx is looking for a hands-on BI Data Developer to design, build, and own the pipelines, models, and governed datasets that power analytics, business decisions, and AI use cases in a fast-moving SaaS environment.

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.
  
  

• 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.
  
  

• 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.