Data Engineer (Azure & Snowflake)

Role Overview

Data Engineer (Azure & Snowflake) building modern cloud-based data solutions for analytics, reporting, automation, and internal AI initiatives.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Azure Data Factory, Snowflake, SQL, and Python
• Build ETL/ELT processes integrating data from enterprise systems, APIs, and third-party sources
• Create reliable datasets and data models for reporting, BI, automation, and AI use cases
• Partner with business stakeholders to gather requirements and translate business needs into technical solutions
• Monitor, troubleshoot, and optimize pipelines for performance, reliability, and data quality
• Perform data validation, testing, and reconciliation to ensure trusted data
• Document data flows, source-to-target mappings, and technical processes
• Collaborate with cross-functional teams to continuously improve cloud data platform practices

Requirements

• 3–5+ years of data engineering / ETL development / data integration experience
• Experience with Snowflake (data modeling, transformations, performance optimization)
• Hands-on Azure Data Factory (pipeline orchestration and workflow management)
• Experience with Azure Data Lake Storage (or similar cloud storage)
• Strong SQL skills (complex queries, performance tuning, large datasets)
• Python for data engineering
• Understanding of data warehousing, ETL/ELT, and dimensional modeling
• Experience integrating data via APIs and handling JSON/XML (or similar formats)
• Experience integrating enterprise SaaS systems such as Salesforce, Workday, GA4, Marketo (or similar)

Preferred

• dbt (or similar modern data transformation framework)
• Supporting AI/ML initiatives with data engineering
• Use of AI-assisted development tools with responsible AI and security practices

Location / Work Setup

• Fully remote work environment
• Role listed in the Rochester, New York Metropolitan Area

Compensation

• $90,000 – $140,000