Azure Data Engineer

Avenica • Chicago, IL, US • 1m ago

Company Summary

Our client is a private family-owned portfolio holding company headquartered in Chicago, Illinois. The portfolio is primarily comprised of several small, independently operated, previously family-run businesses in the light manufacturing and distribution sectors. The company is focused on strategic growth, both organically and through additional acquisitions in the foreseeable future.

The corporate team is composed of senior executives and support staff who provide leadership and guidance to the operating subsidiaries. This team ensures operational, financial, and cultural alignment across the portfolio while maintaining a decentralized business structure that empowers subsidiary leadership.

Position Summary

The Azure Data Engineer will be an experienced Business Intelligence professional with a strong track record of designing, developing, and implementing Data Warehouse and Business Intelligence solutions. The ideal candidate will have expertise in the Microsoft BI stack, including SQL Server, Azure SQL, Azure SQL DW, Azure Synapse Analytics, Azure Storage Account, Azure Data Lake Storage, Azure Databricks, Azure Data Factory (ADF), SSIS, SSRS, SSAS Tabular, and Power BI.

Objectives of this Role

Lead by example with a safety-first mindset.
Collaborate with IT and business stakeholders to define and understand data warehousing requirements.
Design and implement ETL processes to integrate data from multiple systems into the data warehouse.
Ensure data accuracy and integrity through validation and testing of ETL processes.
Develop and maintain data models for the data warehouse.
Be a leader in leveraging tools such as Azure Synapse / Data Factory, Azure Storage, Microsoft SQL Server, Azure DevOps, GitHub, and Power BI to manage data warehouse operations.

Daily and Monthly Responsibilities

Gather requirements from business stakeholders and identify the necessary data from ERP and related systems.
Establish data extraction processes and prepare data for analysis and presentation.
Develop intuitive reports and dashboards in Power BI to support business decision-making.
Create and maintain documentation for data warehouse architecture, data models, and ETL processes.
Review ERP systems and database schemas to facilitate effective data integration.
Stay current with industry trends and advancements in data warehousing technologies.

Education, Experience & Qualifications

Minimum Requirements:

Bachelor’s degree in Information Technology, Computer Science, or a related field (or equivalent experience with a strong financial background and IT skills).
Proven experience in data warehousing, data modeling, and ETL processes.
Strong proficiency in SQL and experience with Microsoft SQL Server.
Expertise in Azure Synapse / Data Factory, Azure DevOps, GitHub, and Power BI.
Experience using SQL Server Management Studio.
Excellent analytical and problem-solving skills.
Strong communication and collaboration abilities.

Skills & Characteristics

Proficiency with SQL and database management, with an understanding of data structures.
Ability to extract, analyze, and interpret data to make informed recommendations.
Strong grasp of database schema structures and relationships.
Experience generating process documentation.
Ability to develop financial reports and dashboards in Power BI.
Strong ability to translate complex data into actionable business insights.
Experience with Microsoft Fabric and related technologies.
Microsoft data certifications (Fabric, Azure Data Engineer) are a plus.

Competency Statements

Analytical Thinking – Ability to analyze complex data sets to identify patterns, trends, and insights that inform business decisions.
Technical Proficiency – Skilled in SQL, data modeling, and using ETL tools to efficiently move and transform data.
Problem-Solving – Capable of troubleshooting and resolving data integrity issues within the data warehouse environment.
Communication – Excellent ability to collaborate with both technical and non-technical stakeholders.
Project Management – Experience managing data projects from conception to completion, ensuring timely and high-quality outcomes.
Innovation – Continuously seeks new ways to improve data processes and warehouse efficiency.
Attention to Detail – Meticulous attention to ensure data accuracy and reliability.
Learning Agility – Quickly adapts to new data technologies and methodologies.
Teamwork – Works collaboratively with cross-functional teams to drive data-driven decision-making across the organization.