Data Engineer

Role Overview

Design, build, and maintain scalable data pipelines and analytics solutions across the company’s Azure cloud environment. Transform raw data from multiple source systems into reliable, business-ready information that powers reporting, analytics, and operational decisions.

Responsibilities

• Design, develop, and maintain ETL/ELT pipelines in Azure to ingest, transform, and integrate data from multiple sources
• Build and optimize Snowflake data solutions for scalable storage, transformation, and analytics workloads
• Manage Azure Data Lake structures for structured and unstructured data
• Develop interactive Power BI dashboards and reports for business intelligence and operational reporting
• Implement integrations connecting Azure, Snowflake, and downstream reporting platforms
• Monitor pipeline performance, troubleshoot failures, and implement enhancements to improve efficiency and reliability
• Ensure data quality, integrity, security, and consistency across cloud data platforms
• Partner with analysts, application developers, and business stakeholders to gather and refine data and reporting requirements

Requirements

• 3+ years hands-on experience in data engineering (or closely related field)
• Demonstrated experience with Snowflake (data loading, transformation, query optimization)
• Proficiency in Microsoft Power BI (dashboard development, report design, data visualization)
• Experience with Azure Data Lake and large-scale datasets
• Strong SQL skills and working knowledge of data modeling and cloud data integration concepts
• Understanding of ETL/ELT and data warehousing principles in Azure environments
• Familiarity with Azure data services and cloud data pipeline performance tuning
• Knowledge of data governance and data security best practices

Nice to Have

• Experience with a scripting/programming language such as Python
• Experience supporting self-service reporting and analytics for business users