Enterprise Analytics Data Engineer

Role Overview

As an Enterprise Analytics Data Engineer at Armanino, you will determine your career path and pursue challenges you are passionate about. You will work in a community of resources that support your ideas, build your skills, and expand your professional network. The role involves building and maintaining curated Gold-layer datasets, reusable analytical data products, and business-ready transformations within Microsoft Fabric.

What You Will Do

Your day-to-day responsibilities will include building and maintaining technical documentation, data mapping, runbooks, release notes, lineage information, and operational procedures. You will also investigate data discrepancies, failed refreshes, model issues, and deployment defects, and document findings clearly. Additionally, you will create and execute practical unit tests, source-to-output reconciliations, regression checks, and deployment validation to confirm grain, joins, totals, historical behavior, and downstream readiness.

Why It Might Be a Fit

To be successful in this role, you will need strong problem-solving skills and learning agility, with a genuine interest in understanding both the technical solution and the business process it supports. You will also need to be able to create and execute practical testing and validation plans that confirm data accuracy, reliability, and deployment readiness. Additionally, you will need to have effective written and verbal communication skills, including the ability to collaborate with senior engineers while independently managing day-to-day work and priorities.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Business Analytics, Engineering, or a related field, or equivalent practical experience.
• Minimum of 2 years of experience in analytics engineering, data engineering, business intelligence engineering, data development, or a closely related technical role.
• Strong working knowledge of SQL, including joins, aggregations, window functions, data profiling, troubleshooting, and source-to-output reconciliation.
• Experience building or supporting analytical datasets, dimensional models, semantic models, reporting data structures, or data transformation workflows.
• Understanding of data engineering and analytics fundamentals, including grain, keys, relationships, transformation logic, data quality, and validation concepts.
• Demonstrated ability to work independently with broad objectives, identify gaps, research solutions, and drive assigned tasks to completion before escalating for assistance.
• Strong problem-solving skills and learning agility, with a genuine interest in understanding both the technical solution and the business process it supports.
• Ability to create and execute practical testing and validation plans that confirm data accuracy, reliability, and deployment readiness.
• Strong attention to detail and appreciation for source control, documentation, operational standards, and maintainable engineering practices.
• Effective written and verbal communication skills, including the ability to collaborate with senior engineers while independently managing day-to-day work and priorities.

Benefits

• Medical, dental, vision
• Generous PTO plan and paid sick time
• Flexible work arrangements
• 401K with Profit Sharing
• Wellness program
• Generous parental leave
• 11 paid holidays

Tagged as: Data Analysis, SQL