Data Engineer

About the Role

eNGINE is hiring a Data Engineer for a growing organization operating an online marketplace and digital distribution platform supporting the HVAC and building automation industry. This is a greenfield opportunity to become the company’s founding Data Engineer, working directly with the VP of Engineering to modernize data infrastructure, establish data strategy, and build a scalable Snowflake-based platform from the ground up.

Key Responsibilities

• Architect, build, and own a modern data platform centered around Snowflake and a Bronze/Silver/Gold Medallion Architecture.
• Develop ELT pipelines using Airbyte, Fivetran, or similar technologies to ingest data from Salesforce, HubSpot, Acumatica, Dialpad, SQL databases, GA4, and additional operational systems.
• Build and maintain dbt Core models across staging, transformation, and business-facing Gold layers.
• Create unified customer, product, revenue, pipeline, inventory, and margin data models.
• Develop Python-based data synchronization jobs between operational platforms.
• Integrate with Salesforce REST/Bulk APIs, HubSpot APIs, and other enterprise applications.
• Own pipeline monitoring, alerting, failure recovery, data freshness, and reconciliation.
• Establish data quality standards, automated testing, lineage, documentation, and governance practices.
• Build APIs using Python/FastAPI to expose Snowflake data to internal applications.
• Design data access controls, including role-based and row-level security.
• Build and support executive and operational dashboards using tools such as Streamlit, Sigma, Tableau, Power BI, or Looker.
• Partner directly with engineering and business leadership to translate business requirements into scalable data solutions.
• Support the migration away from legacy Azure SQL dependencies while maintaining continuity of existing systems.
• Document architectural decisions and establish repeatable engineering standards as the data environment grows.

Requirements & Tech Stack

• Strong hands-on experience with Snowflake, including schema design, performance optimization, warehouse sizing, clustering, and cost management.
• Production experience with dbt Core, including modular models, macros, incremental models, packages, testing, and documentation.
• Experience building multi-source ELT pipelines with Airbyte, Fivetran, or similar tools.
• Strong Python development experience for data pipelines, integrations, API clients, and automation.
• Expert-level SQL, including complex joins, CTEs, window functions, and data modeling.
• Experience working with Azure, particularly Azure SQL, storage, and deployment pipelines.
• Experience integrating with Salesforce APIs, including REST/Bulk APIs, SOQL, and external IDs.
• Experience implementing automated data quality checks, monitoring, and reconciliation.
• Ability to operate with a high level of ownership in a fast-moving environment with limited existing structure.
• Strong documentation habits and the ability to communicate technical decisions to both engineering and business stakeholders.

Nice to Have

• Experience in B2B distribution, manufacturing, eCommerce, HVAC, or another product/inventory-heavy environment.
• HubSpot API experience.
• GA4 and BigQuery experience.
• FastAPI experience.
• Streamlit or Snowflake-native application development.
• Experience with Tableau, Sigma, Power BI, or Looker.
• CI/CD experience for data pipelines using GitHub Actions, Bitbucket Pipelines, or similar.
• Experience migrating from SQL Server or Azure SQL Managed Instance into a modern cloud data platform.
• Experience working through a Strangler Fig or parallel-run migration strategy.
• Experience designing executive-facing dashboards and KPI reporting.

Why This Opportunity?

This is a non-maintenance Data Engineer position. You will join an organization investing heavily in technology and modernization, with the opportunity to establish data engineering practices across the company. As the first Data Engineer, you will have significant ownership over architecture, tooling, modeling standards, governance, integrations, and reporting infrastructure. The ideal candidate brings a startup mentality — curious, comfortable working without a predefined playbook, willing to solve problems outside a narrow job description, and motivated by building from the ground up. The company offers a 5% 401(k) match, with an additional 4% profit-sharing contribution after one year.