Data Engineer (Azure & Snowflake)

Mindex•Rochester, NY

21h•Remote

About The Position

Mindex is looking for a Data Engineer who enjoys building modern cloud-based data solutions that help organizations make smarter business decisions. In this role, you'll develop scalable data pipelines, integrate data from multiple business systems, and deliver reliable datasets that power analytics, reporting, automation, and internal AI initiatives. You'll partner with business and technical stakeholders to understand data needs, design practical solutions, and ensure data is accurate, accessible, and ready for decision-making. The ideal candidate enjoys solving complex data challenges, writing clean and efficient code, and building dependable data platforms in Azure and Snowflake.

Requirements

3 - 5+ years of experience in data engineering, ETL development, or data integration.
Experience working with Snowflake or another modern cloud data warehouse, including data modeling, transformations, and performance optimization.
Hands-on experience with Azure Data Factory or a similar cloud-based orchestration tool, including pipeline orchestration and workflow management.
Experience working with Azure Data Lake Storage or similar cloud storage platforms.
Strong SQL skills, including writing complex queries, optimizing performance, and working with large datasets.
Experience developing data solutions using Python.
Understanding of data warehousing concepts, ETL/ELT processes, and dimensional modeling.
Experience integrating data through APIs and working with JSON, XML, or similar data formats.
Experience integrating enterprise SaaS applications such as Salesforce, Workday, GA4, Marketo, or similar business systems.

Nice To Haves

Experience with dbt or similar modern data transformation frameworks.
Experience supporting AI or machine learning initiatives through data engineering.
Experience using AI-assisted development tools while following responsible AI and security practices.

Responsibilities

Design, develop, and maintain scalable data pipelines using Azure Data Factory, Snowflake, SQL, and Python.
Build ETL and ELT processes that integrate data from enterprise applications, APIs, and third-party systems.
Develop reliable datasets and data models that support reporting, business intelligence, automation, and AI initiatives.
Partner with business stakeholders to gather requirements and translate business needs into technical solutions.
Monitor, troubleshoot, and optimize data pipelines to ensure performance, reliability, and data quality.
Perform data validation, testing, and reconciliation to ensure accurate and trusted data.
Document data flows, source-to-target mappings, and technical processes to support ongoing maintenance and knowledge sharing.
Collaborate with cross-functional teams to continuously improve the organization's cloud data platform and engineering practices.