Business Intelligence Engineer

Role Overview

The Business Intelligence (BI) Engineer will design, build, and maintain finance and customer analytics pipelines. The focus is on creating a modular, scalable data foundation using dbt and delivering curated data models for analytics and semantic layer use cases.

Responsibilities

• Use dbt to:
  • Design modular data models
  • Enforce data quality and quality tests
  • Document transformations
  • Collaborate via Git and deploy dbt pipelines to production
• Architect layered dbt models (e.g., staging → intermediate → marts) for finance and customer master data.
• Build a unified data model by integrating and transforming data from diverse sources.
• Create models that act as a business rules framework to reduce reliance on external rules engines and streamline governance.
• Develop and maintain standardized/conformed entities (e.g., Client, Customer, Billing) to support Gold analytics and semantic models.
• Deliver certified data products and contribute to the DBT semantic layer (reusable dimensions, certified metrics, exposures, macros).
• Provide self-service analytics capabilities in Snowflake.
• Define and maintain technical metadata standards (e.g., lineage and technical definitions).
• Apply dbt best practices:
  • Modular packages
  • Jinja logic
  • Documentation standards
• Collaborate with BI product owners, data analysts, and governance teams to apply consistent business logic across reporting tiers.
• Define and implement business-aligned data quality rules and certification standards.
• Partner with data governance to steward definitions, metrics, and lineage.

Requirements

• ~4 years of experience building engineering analytics pipelines (SaaS environment preferred).
• 1 year of experience using dbt for modular model design, data quality enforcement, documentation, Git collaboration, and production deployments.
• Advanced SQL skills (CTEs, window functions, recursion).
• Experience with modern cloud data warehouses (e.g., Snowflake, BigQuery, Redshift, Databricks).
• Strong knowledge of data modeling techniques (e.g., star schema, Snowflake schema, data vault).

Preferred Qualifications

• Experience with dbt Cloud IDE.
• Data visualization experience ( Power BI preferred).
• Familiarity with Snowflake and dbt CI/CD automation using GitHub Actions.
• Agile delivery mindset (backlog management via Jira) and cross-functional stakeholder leadership.
• Experience with business systems such as Salesforce, NetSuite, or Zuora.
• Exposure/training in Snowflake concepts (e.g., Snowflake Data Warehousing Workshop – Badge 1).

Education

• Bachelor’s degree in Data Analytics, Computer Science, Information Technology, Finance, or related field.