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Position: Senior Data Engineer
Location: Woodbury, NY/Calhoun, GA (Onsite)
Duration: Full Time

Woodbury, NY 11797 or Calhoun, GA 30701

& GC 

Experience- 10+ Yrs

A detailed write-up is required explaining how the candidate’s experience aligns with the role, company sizes/background of prior employers, and distance/commute information to the work location.

Work Model: First 6 months fully onsite, then minimum 3 days onsite/remains remote. Woodbury, NY candidates must be within a realistic commuting distance; NJ candidates will not be considered.

Focus: Microsoft Fabric, ETL, and Enterprise Data Warehouse

Role Summary

The Senior Data Engineer will own the design, implementation, and evolution of Client’s enterprise data platform, including ETL pipelines, data warehouse/Lakehouse architecture, and enterprise data modeling. This role will lead the transition from an on-premises SQL environment to a scalable Microsoft Fabric cloud analytics platform, driving future growth, advanced analytics, and self-service BI capabilities. This is a small team environment, requiring candidates who can work independently and are comfortable wearing multiple hats; candidates from large enterprise-only environments are not preferred. Client is a mid-sized organization with approximately $200–300M in annual sales.

Core Responsibilities

• End-to-end ownership of data pipelines, models, and analytics architecture — from design through production support
• Acts as the technical decision-maker for data platform standards and patterns
• Comfortable operating in environments with evolving requirements and incomplete data
• Ability to translate available data from pipelines into value-added analytics to the business’s benefit
• Expected to proactively identify business solutions, data gaps, quality issues, and architectural improvements
• Design and implement the Microsoft Fabric Lakehouse and data warehouse, and lead the transition from on-premises SQL-based solutions
• Develop and maintain ETL and ELT pipelines using Fabric Data Factory, SQL, and notebooks
• Ability to define and establish the semantic layer to enable servicing data to business resources for self-service visualizations
• Apply scripting or notebook-based approaches, including Python/R/etc. where appropriate, for data transformation, automation, and data quality enforcement
• Integrate data from AS400 ERP, Salesforce, HubSpot, and other SaaS platforms
• Design analytical data models, fact and dimension tables, and curated data marts
• Implement CI/CD practices for data pipelines and analytics assets, enabling agile, reliable, and controlled production deployments
• Operate in an Agile delivery environment
• Optimize platform performance, scalability, reliability, and cost
• Support and stabilize existing datasets and dashboards
• Drive Power BI adoption and define migration approach for legacy tools and standards
• Design and implement data quality checks, monitoring, alerting, recovery mechanisms, and governance controls
• Maintain documentation for pipelines, models, and integration patterns
• Partner with IT and business stakeholders to translate requirements into data solutions

Required Qualifications

• Bachelor’s degree in Computer Science, Information Systems, or equivalent experience
• 6+ years of experience in data engineering, including enterprise data warehouse and analytics platforms
• Advanced SQL skills with strong analytical and enterprise data modeling experience
• Experience designing and operating data warehouses, lakes, or Lakehouse architectures in a cloud environment
• Excellent communication skills with the ability to engage directly with technical and business stakeholders and recommend impactful business and architectural solutions.
• Experience integrating ERP systems, CRM, and SaaS data sources
• Experience supporting BI tools, including Tableau (phasing out) and Power BI
• Stable work history required; no career consultants/serial short-term project candidates.
• Manufacturing/Distribution industry exp required

Preferred Experience

• Azure Synapse, Data Factory, or Databricks
• Salesforce and HubSpot data models and APIs
• Data governance, quality frameworks, and access controls