Analytics Engineer

Job Title: Analytics Engineer (Data Analyst & Bi Developer) 

Department: IT 
Location: Remote

About the Role

This is a high-impact, independent contributor role at the heart of our SaaS business transformation. We are seeking a proactive builder—not a passive analyst—who will actively seek out opportunities, identify gaps, and deliver solutions that move the business forward. You will not wait to be told what to do; you will own the data lifecycle and be a key driver of our data strategy. As a key member of a new and growing team, you’ll help establish our single, trusted analytical layer within Microsoft Fabric and empower every team member with actionable insights.

We are seeking a proactive builder—not a passive analyst. You will actively identify gaps, deliver solutions, and drive the data lifecycle. As a key member of a growing team, you’ll help establish our single, trusted analytical layer within Microsoft Fabric and empower every team member with actionable insights.

How You’ll Make a Difference

• Drive, Don’t Wait: Actively seek out business needs, identify opportunities for improvement, and deliver solutions—rather than waiting for assignments.
• Own the Data Lifecycle: Proactively engage with business stakeholders (Sales, Finance, Customer Success, Product, etc.) to pull requirements and translate complex business questions into technical data models.
• Single Source of Truth (SSoT): Collaboration with Data Engineer to design, develop, and maintain a unified Customer 360 Single Source of Truth by integrating and transforming data from diverse SaaS applications (CRM, billing, CLM, product usage, etc.).
• BI Development: Build and deploy high-impact Power BI dashboards and reports that visualize key SaaS metrics (MRR, Churn, CAC, LTV, product adoption) and drive measurable business outcomes.
• Self-Service Enablement: Develop robust, secure, and well-documented datasets in Power BI to facilitate self-service analytics and data literacy across the organization.
• Champion Data Stewardship: Promote best practices for data quality, documentation, and governance, ensuring analytical assets are reliable and trusted.
• Data Modeling: Architect and build high-performance, structured dimensional models within Microsoft Fabric, optimized for analytics.
• Data Transformation: Develop, test, and deploy production-grade data transformation logic using advanced SQL and Python/PySpark Notebooks.
• Automation (Bonus): Familiarity with Microsoft Power Apps and Power Automate is a plus, helping streamline and automate manual data and reporting workflows.

What You Bring

• Proactive Ownership: You are a self-starter who thrives in ambiguity, takes initiative, and drives projects independently—without waiting for direction.
• 3+ years of progressive experience as a Data Analyst, BI Developer, or Analytics Engineer, ideally in a SaaS or technology business.
• Microsoft Data Stack Expertise: Deep, hands-on experience with Microsoft Fabric, Power BI (advanced DAX, modeling, security), and advanced SQL.
• Programming Skills: Strong capability in Python/PySpark for data transformation and pipeline development.
• Data Modeling: Expert understanding of dimensional modeling (Kimball methodology) and scalable data warehouse solutions.
• SaaS Metrics: Familiarity with core SaaS/subscription business metrics and the data structures required to calculate them.
• Communication: Exceptional written and verbal communication skills, able to bridge technical and business concepts.
• Agile Mindset: Comfortable working in a fast-paced, iterative environment and collaborating with cross-functional teams.

Success in This Role Means

• You function as the end-to-end owner of data solutions, from requirements gathering to dashboard deployment.
• The Customer 360 SSoT becomes the trusted, go-to source for strategic reporting and decision-making.
• Staff spend less time searching for and preparing data, and more time solving customer problems.
• Data is accessible, reliable, and drives the adoption of self-service analytics.
• Measurable improvements in data quality, accessibility, and dashboard usage.