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Armanino

Enterprise Analytics Data Engineer

Armanino

. Build and maintain curated Gold-layer datasets, reusable analytical data products, and business-ready transformations within Microsoft Fabric.

Posted 11/10/2026full-timeUnited StatesJuniorMid-Level💰 $90,000 - $125,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in SQL, Power BI, and Microsoft Fabric for building and maintaining analytical datasets and semantic models. Strong problem-solving abilities and effective communication skills are essential for collaborating with stakeholders and driving independent engineering tasks.

Highest-signal resume keywords
SQL ProficiencyPower BI Semantic ModelsMicrosoft Fabric ComponentsData Transformation WorkflowsAnalytical Dataset Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
SQLDAXPythonSparkData ProfilingData ValidationDimensional ModelingData QualityTesting and Validation PlansData Transformation
Soft Skills
Problem-SolvingAttention to DetailEffective CommunicationLearning AgilityIndependent Work
Tools & Technologies
Microsoft FabricPower BIGitAzure DevOpsCI/CD
Industry Keywords
Analytics EngineeringBusiness Intelligence EngineeringData EngineeringData DevelopmentGold-Layer Data Products

Tech Stack

Tools & technologies
AzurePySparkPythonSparkSQL

About the role

Key responsibilities & impact
  • Build and maintain curated Gold-layer datasets, reusable analytical data products, and business-ready transformations within Microsoft Fabric.
  • Translate business requirements and source-system data into well-structured facts, dimensions, conformed attributes, and governed business logic that support enterprise analytics.
  • Develop, enhance, and support Power BI semantic models, including relationships, measures, calculated logic, row-level security, refresh behavior, and performance considerations.
  • Own low to moderate-complexity engineering work with limited day-to-day direction, researching solutions and driving assigned work from requirements through validation and release.
  • Partner closely with senior analytics engineers to learn established architecture and development patterns, absorb repeatable work, and expand independent ownership over time.
  • Use SQL and, as appropriate, Python, Spark, notebooks, DAX, or Power Query to transform, validate, troubleshoot, and reconcile analytical data.
  • 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.
  • Participate in Git-based development practices, including branches, pull requests, peer reviews, work-item traceability, and controlled promotion through development, test, and production environments.
  • Learn and contribute to CI/CD, Microsoft Fabric deployment pipelines, release automation, environment configuration, and repeatable deployment evidence.
  • Investigate data discrepancies, failed refreshes, model issues, and deployment defects; document findings clearly, resolve routine problems, and escalate complex issues with relevant diagnostic evidence.
  • Create and maintain technical documentation, data mapping, runbooks, release notes, lineage information, and operational procedures that make solutions supportable and repeatable.
  • Collaborate with Enterprise Analytics & Insights, DataOps, governance, consultants, and business stakeholders while maintaining clear ownership of assigned day-to-day work.
  • Apply established naming, security, documentation, change-management, monitoring, and engineering standards, and recommend practical improvements as experience grows.

Requirements

What you’ll need
  • 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.
  • Preferred: hands-on experience with Microsoft Fabric components such as lakehouses, warehouses, notebooks, data pipelines, semantic models, deployment pipelines, monitoring, or capacity concepts.
  • Preferred: experience with Power BI semantic models and DAX, including relationships, filter context, totals, time intelligence, row-level security, and performance troubleshooting.
  • Preferred: familiarity with dimensional modeling and medallion architecture, particularly the development of curated Gold-layer data products from governed Bronze and Silver foundations.
  • Preferred: experience with Python, PySpark, Spark SQL, Fabric notebooks, Power Query, or comparable data transformation technologies.
  • Preferred: experience using Git, branching strategies, pull requests, code reviews, and work-item-linked development practices.
  • Preferred: exposure to Azure DevOps, GitHub, CI/CD, deployment automation, infrastructure-as-code, environment configuration, or release governance.
  • Preferred: experience documenting data lineage, business rules, data contracts, technical designs, runbooks, or deployment procedures.
  • Preferred: experience working in an evolving environment where architecture, standards, and processes are being established while active delivery continues.

Benefits

Comp & perks
  • 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
  • Eligible employees at certain levels can participate in a discretionary long-term financial incentive plan, subject to plan participation rules