Analytics Engineer

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 and work with business and system owners to resolve

Document data lineage, transformation logic, KPI definitions, solution architecture, dependencies, support procedures, and intended consumption across reports, self-service, and AI-enabled solutions.

Follow and help strengthen standards for naming, security, access, testing, deployment, and lifecycle

Promote reuse, consistency, business ownership, and responsible use of data across the

Delivery, Support & Continuous Improvement

Own solutions through discovery, design, development, testing, deployment, adoption, and ongoing

Work within source control and CI/CD practices to deliver reliable, traceable changes across

Troubleshoot data, model, refresh, and report issues and perform root-cause

Identify opportunities to reduce manual reporting, retire duplicate solutions, expand self-service, and apply AI or automation where it provides practical business value.

Share knowledge with teammates and business users through documentation, demonstrations, and working

Qualifications

Required

Bachelor’s degree in Information Systems, Computer Science, Data Analytics, Engineering, Business Analytics, or a

related field, or equivalent practical experience.

Professional experience in analytics engineering, business intelligence, data engineering, or a similar

Demonstrated ability to gather requirements, understand business processes, and translate needs into technical

Strong experience developing enterprise data and analytics solutions, including semantic models, DAX, and Power BI delivery.

Strong SQL skills and experience working with relational and analytical data

Experience building or supporting ETL/ELT processes, data pipelines, and data

Knowledge of dimensional modeling, star schemas, data warehousing, and data quality

Ability to communicate effectively with business stakeholders, technical teams, and

Ability to manage multiple priorities, work independently, and take ownership of

Preferred

Hands-on experience with Microsoft Fabric, including Data Factory pipelines, Lakehouse, Warehouse, notebooks, and semantic models.

Experience developing data transformations or automation using Python or

Experience with Git, Azure DevOps, deployment pipelines, testing, and CI/CD

Experience integrating data from REST APIs, SaaS platforms, SQL Server, and cloud-based

Experience with data governance, lineage, metadata, access controls, KPI or data-dictionary management, and preparing governed data for self-service or AI use cases.

Experience supporting enterprise functions such as Finance, Sales, Project Management, Human Resources, Health & Safety, or Operations.

Experience in the architecture, engineering, construction, environmental, or professional-services

Familiarity with project-based business metrics such as backlog, utilization, revenue, profitability, project performance, and resource planning.

Core Competencies

Business partn