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eNGINE · Pittsburgh
eNGINE builds Technical Teams. We are a Solutions and Placement firm shaped by decades of interaction with Technical professionals. Our inspiration is continuous learning and engagement with the markets we serve, the talent we represent, and the teams we build.
We are hiring a Data Engineer for a growing organization that operates an online marketplace and digital distribution platform supporting the HVAC and building automation industry.
This is a greenfield opportunity and a chance to become the company’s founding Data Engineer. You will work directly with the VP of Engineering to modernize the company’s data infrastructure, establish its data strategy, and build a scalable Snowflake-based platform from the ground up.
What You’ll Do
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
What We’re Looking For
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 not a maintenance-focused Data Engineer position. You will be joining an organization that is investing heavily in technology and modernization and will have the opportunity to establish how data engineering is done across the company.
As the first Data Engineer on the team, you will have significant ownership over architecture, tooling, modeling standards, governance, integrations, and reporting infrastructure. The ideal candidate brings a startup mentality — someone who is naturally curious, comfortable working without a predefined playbook, willing to solve problems outside a narrow job description, and motivated by building something from the ground up.
The company offers a 5% 401(k) match, with an additional 4% profit-sharing contribution after one year.
No C2C candidates will be considered.
Apply today to learn more.
Details
| Company | eNGINE |
| Location | Pittsburgh |
| Type | FULL TIME |
| Niche | Computer and Mathematical Occupations |