Analytics Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate with business leaders, subject-matter experts, and end users to comprehend processes, challenges, objectives, and reporting requirements.

• Facilitate discovery and requirements-gathering sessions; document business rules, data definitions, use cases, acceptance criteria, and success metrics.

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

• Provide guidance to stakeholders on KPI design, metric consistency, solution alternatives, and suitable reporting, self-service, automation, or AI-enabled experiences.

• Convey solution alternatives, trade-offs, progress updates, and risks to both technical and non-technical audiences.

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

• Build and maintain semantic models, relationships, hierarchies, calculations, and DAX measures.

• Validate KPIs, reconcile outcomes, and establish reliable analytics outputs.

• Enable governed self-service analytics and AI readiness through certified data assets, thorough documentation, and user training.

• Design, build, and manage Microsoft Fabric data pipelines, notebooks, lakehouses, warehouses, and associated components.

• Develop ingestion and transformation processes utilizing SQL, Python, Fabric Data Factory pipelines, and related tools.

• Construct and maintain Bronze, Silver, and Gold data layers.

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

• Implement monitoring, validation, error handling, and enhancements in performance.

• Design dimensional models, star schemas, curated data marts, and analytical models.

• Profile and validate source data; identify and resolve data-quality challenges.

• Document data lineage, transformation logic, KPI definitions, architecture, dependencies, support procedures, and intended usage.

• Adhere to and enhance standards for naming conventions, security, access, testing, deployment, and lifecycle management.

• Own solutions through the phases of discovery, design, development, testing, deployment, adoption, and ongoing support.

• Operate within source control and CI/CD practices.

• Troubleshoot issues related to data, models, refreshes, and reports while conducting root-cause analysis.

• Identify opportunities to minimize manual reporting, retire duplicate solutions, expand self-service capabilities, and leverage AI or automation.

• Share knowledge through documentation, demonstrations, and collaborative sessions.

⛳️ Requirements

• 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 related field.

• Proven ability to gather requirements, understand business processes, and convert needs into technical solutions.

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

• Strong SQL expertise and experience with relational and analytical databases.

• Experience in building or supporting ETL/ELT processes, data pipelines, and data integrations.

• Understanding of dimensional modeling, star schemas, data warehousing, and data quality practices.

• Ability to effectively communicate with business stakeholders, technical teams, and vendors.

• Capacity to manage multiple priorities, work independently, and take ownership of deliverables.

• Preferred: hands-on experience with Microsoft Fabric, including Data Factory pipelines, Lakehouse, Warehouse, notebooks, and semantic models.

• Preferred: experience in developing data transformations or automation using Python or PySpark.

• Preferred: familiarity with Git, Azure DevOps, deployment pipelines, testing, and CI/CD practices.

• Preferred: experience integrating data from REST APIs, SaaS platforms, SQL Server, and cloud-based systems.

• Preferred: knowledge of data governance, lineage, metadata, access controls, KPI or data-dictionary management, and governed data for self-service or AI applications.

• Preferred: experience supporting enterprise functions such as Finance, Sales, Project Management, Human Resources, Health & Safety, or Operations.

• Preferred: experience in architecture, engineering, construction, environmental, or professional-services organizations.

• Preferred: familiarity with project-based business metrics such as backlog, utilization, revenue, profitability, project performance, and resource planning.

• Technology environment includes Microsoft Fabric, Power BI, SQL, DAX, Fabric Data Factory, pipelines, notebooks, Lakehouse, Warehouse, semantic models, APIs, Git, and Azure DevOps.

🏝️ Benefits

• All Apex positions are eligible for annual bonus opportunities.

• Company-subsidized medical and dental coverage.

• Company-paid life, short-term, and long-term disability insurance.

• 401(k) matching program.

• Tuition assistance program.

• Opportunities for cross-training.

• Experience working on a diverse range of projects.

• Performance-based bonuses or other incentives.