Analytics Engineer

Apex Companies · Remote

  • Junior
  • Full-time
  • $120,000 – $150,000
  • Posted 2026-09-24
  • Confirmed live on 25 September 2026

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Job description

Are you driven to grow, lead, and make a meaningful impact? At Apex, we’re building more than a consulting and engineering firm—we’re creating a place where your career accelerates, your contributions matter, and your potential is fully realized. We believe your growth is our growth, which is why we invest in your development at every stage of your career. Here, you’ll work on projects that shape communities, protect the environment, and create lasting impact, all while being empowered with the autonomy and flexibility to do your best work.

Fueled by high-quality delivery, exceptional client retention, and strategic acquisitions, Apex Companies continues to rank among the fastest-growing firms in the AEC industry, recently recognized by the Zweig Group for our industry-leading growth. Our success is grounded in strong leadership, a collaborative culture, and a shared commitment to delivering exceptional outcomes.

As we continue to expand, we're looking for high-performing professionals who are ready to lead, collaborate, innovate, and create impact. At Apex, you help shape what's next. When we succeed together, we share in that success. All Apex positions are eligible for annual bonus opportunities, reinforcing our commitment to recognizing and rewarding meaningful contributions that drive our collective growth.

Role Overview

We are seeking an Analytics Engineer to join our Corporate Data & Analytics team. This role combines business partnership, analytics development, and data engineering to deliver scalable, governed data solutions across the organization. These solutions will support enterprise analytics, governed self-service, and emerging AI-enabled experiences.

The Analytics Engineer will work closely with business stakeholders to understand operational challenges, gather and document requirements, define meaningful KPIs, and translate those needs into reliable data products. This individual will design, develop, and maintain end-to-end solutions within Microsoft Fabric, including pipelines, notebooks, lakehouses, warehouses, data models, and semantic models. Power BI will remain an important delivery channel, while the broader focus is creating trusted, reusable data products that can support reporting, self-service analytics, AI assistants, agents, APIs, and future business applications.

The ideal candidate can move comfortably between business conversations and hands-on technical delivery, explain complex concepts clearly, and build solutions that are accurate, maintainable, and easy for the business to use.

Key Responsibilities

Business Partnership & Solution Design

• Partner with business leaders, subject-matter experts, and end users to understand business processes, challenges, goals, and reporting needs.

• Lead discovery and requirements gathering sessions; document business rules, data definitions, use cases, acceptance criteria, and success measures.

• Translate business needs into scalable data solutions, including curated data products, semantic models, self-service datasets, dashboards, AI-ready data assets, and operational reporting.

• Advise stakeholders on KPI design, metric consistency, solution options, and when reporting, self-service, automation, or AI-enabled experience best fit the business need.

• Communicate solution options, tradeoffs, progress, and risks clearly to both technical and non-technical

Data Products, Semantic Models & Analytics Experiences

• Design and build reusable data products and semantic models that support Power BI reports, dashboards, scorecards, self-service analytics, and future AI-enabled experiences.

• Develop and maintain reusable semantic models, relationships, hierarchies, calculations, and business

• Create and optimize DAX measures with a focus on accuracy, performance, consistency, and

• Partner with business owners to validate KPIs, reconcile results, and establish trusted

• Enable governed self-service analytics and AI readiness through certified data assets, business-friendly semantic models, clear documentation, and user education.

Microsoft Fabric & Data Engineering

• Design, build, and support data pipelines, notebooks, lakehouses, warehouses, and related components within Microsoft

• Develop ingestion and transformation processes using SQL, Python, Fabric Data Factory pipelines, and

• Build and maintain Bronze, Silver, and Gold data layers using reusable, domain-aligned patterns that support reporting, self-service analytics, and trusted AI consumption.

• Integrate data from enterprise applications, APIs, files, cloud platforms, and on-premises

• Implement monitoring, validation, error handling, and performance improvements to support dependable production solutions.

Data Modeling, Quality & Governance

• Design dimensional models, star schemas, curated data marts, and analytical models that support scalable enterprise reporting.

• Profile and validate source data; identify quality issues a

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