Data Engineer (Azure & Snowflake) - Remote

Mindex is a company that has been solving complex business challenges for over 30 years through custom software and data solutions. They are seeking a Data Engineer who will develop scalable data pipelines and integrate data from various business systems to support analytics and AI initiatives.

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

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
• 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