Data Engineer Location:

Pittsburgh, PA About eNGINE 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. Our Consulting Workforce is encouraged to enjoy career fulfillment in the form of challenging projects, schedule flexibility, and paid training/certifications. Successful outcomes start and finish with eNGINE. Role Overview eNGINE is seeking a Data Engineer to play a foundational role in a major modernization of an established Pittsburgh-based technology organization. The company operates a digital marketplace and distribution platform serving large commercial builders in the HVAC and building automation controls space. Following significant investment in growth, the Engineering organization is building the technology and data capabilities needed to support the next phase of the business, including opportunities in the rapidly expanding data center construction market. This position will be the first dedicated Data Engineer focused on this initiative, providing an opportunity to take ownership of the data architecture and build a modern platform from the ground up. You will design and implement a scalable data ecosystem that brings information together from CRM, marketing, ERP, product, communications, and web analytics platforms. The resulting Snowflake environment will support executive reporting, operational analytics, AI initiatives, and internal applications. This is a highly hands-on role. You will have significant ownership over architecture, pipelines, data modeling, quality, integrations, and the evolution away from legacy data infrastructure. Responsibilities Data Engineering & Architecture Design and build reliable ELT pipelines that consolidate data from multiple operational systems into Snowflake Develop scalable ingestion processes using technologies such as Airbyte, Fivetran, or comparable platforms Build Python-based data integration and synchronization processes between business applications Design incremental data ingestion strategies for high-volume datasets and APIs Establish monitoring, alerting, and recovery processes to ensure data pipelines remain reliable and current Make architectural decisions around data storage, transformation, performance, scalability, and cost Data Modeling & Snowflake Build and maintain a Snowflake-based Bronze, Silver, and Gold data architecture Develop dbt models that clean, standardize, deduplicate, and transform data from disparate source systems Create unified customer and product data models that connect information across CRM, ERP, operational, and marketing platforms Develop curated data marts supporting areas such as customer analytics, sales performance, revenue attribution, pipeline health, inventory, margins, vendor performance, and web-to-revenue analysis Optimize Snowflake schemas, warehouses, clustering, and query performance Establish automated testing, documentation, and lineage across the data platform Data Integration & System Synchronization Develop and maintain integrations between internal operational systems, Salesforce, HubSpot, and other business applications Build resilient synchronization processes that account for incremental updates, retries, duplicate prevention, and failed transactions Work with Salesforce APIs, including REST/Bulk APIs and SOQL, to move and synchronize operational data Support the integration of product, inventory, vendor, customer, opportunity, order, and other business data Partner with application and business teams to determine how data should move between systems Data Quality & Governance Establish data quality standards and validation processes across source systems and analytical models Implement automated checks to identify missing, invalid, inconsistent, or stale data before it reaches business users Develop processes for reconciling information across systems and identifying discrepancies Document data definitions, ownership, lineage, validation practices, and architectural decisions Establish clear expectations around data freshness, accuracy, and availability Application & Analytics Enablement Build data APIs using Python and FastAPI to make curated Snowflake data available to internal applications Support internal application functionality including customer views, pipeline analytics, inventory risk, and margin reporting Develop data-backed dashboards and reporting solutions using platforms such as Streamlit, Sigma, Tableau, Power BI, or comparable tools Partner with business leadership to translate analytical requirements into well-designed data models and reporting solutions Enable business users to access trusted data and answer questions without requiring advanced SQL expertise Implement appropriate role-based and row-level access controls for sensitive business information Legacy Modernization Help transition the organization from fragmented legacy data processes to a modern, scalable data architecture Work alongside the Engineering team to reduce dependencies on legacy Azure SQL infrastructure and move appropriate workloads toward Snowflake Support the evolution and integration of the organization's Product Information Management capabilities Maintain appropriate legacy functionality during migration while progressively introducing modern replacements Document key architectural decisions and technical approaches to establish sustainable knowledge within the Engineering organization Required Qualifications Strong professional experience as a Data Engineer, with significant hands-on development experience Deep practical experience with Snowflake, including data architecture, schema design, warehouse management, performance optimization, and cost considerations Production experience with dbt Core, including modular models, incremental processing, macros, packages, testing, and documentation Experience implementing multi-source ELT pipelines using Airbyte, Fivetran, or comparable technologies Strong Python development skills for data engineering, APIs, integrations, and automation Advanced SQL skills, including complex joins, CTEs, window functions, and analytical transformations Practical experience with Azure and cloud-based data infrastructure Experience working with Azure SQL Managed Instance or SQL Server Hands-on experience integrating with the Salesforce API, including REST/Bulk APIs, SOQL, and API limitations Experience implementing data quality, monitoring, and validation processes Strong understanding of data architecture, data modeling, and modern analytics platforms Demonstrated ability to take ownership of projects and make sound technical decisions independently Strong documentation and communication skills Preferred Experience Experience working with B2B, distribution, manufacturing, product, inventory, or other product-centric data Experience with HubSpot APIs and CRM/marketing data integrations Experience with Google Analytics 4 and BigQuery, including GA4 export data and attribution analysis Experience building internal data services with FastAPI Experience migrating from on-premises SQL Server or Azure SQL environments to modern cloud data platforms Experience implementing parallel-run or incremental legacy modernization strategies Experience with CI/CD for data engineering, including GitHub Actions, Bitbucket Pipelines, or comparable tooling Experience with Streamlit and/or Snowflake-native analytics applications Experience with Sigma, Tableau, Power BI, Looker, or other BI platforms connected to Snowflake Experience developing executive-facing dashboards with KPIs, drill-downs, trends, and operational metrics Next Steps No C2C, relocation, referral, or sponsorship candidates for this role. For finer details on how eNGINE can impact your career, apply today!

Pay:

$135,000.00 - $155,000.00 per year

Benefits:

401(k) 401(k) matching Life insurance Paid time off Vision insurance

Work Location:

In person