Analytics Engineer

Axis Residential is a forward-thinking, property management organization, part of Inland Group – a vertically integrated real estate developer, contractor, and operator of multifamily and senior housing communities. Collectively, we have set ourselves apart as an industry leader who genuinely cares for the well‑being and success of our people while creating an environment of meaningful community for our residents. Our success is a result of our team and culture– we take a relational and entrepreneurial approach to business and our team members are authentic, curious, natural leaders who value the greater team.

We love what we do, and we are committed to excellence in our work.

The Analytics Engineer is responsible for designing, building, and maintaining the organization’s analytics and business intelligence solutions. This role bridges the gap between raw data and business decision‑making by developing reliable semantic models, scalable Power BI dashboards, and actionable insights across multiple data platforms. The ideal candidate is equally comfortable working in Power BI, while also possessing strong analytical and communication skills.

This role partners closely with business leaders, IT, and data stakeholders to ensure data is trusted, accessible, and meaningfully translated into insights that drive operational and strategic decisions.

• Design, develop, and maintain Power BI dashboards and reports that provide clear, actionable insights to business stakeholders.
• Build and manage semantic data models optimized for analytics, performance, and self‑service reporting.
• Translate business questions and requirements into analytical solutions, KPIs, and metrics.
• Analyze trends, patterns, and anomalies in data and clearly articulate findings to technical and non‑technical audiences.

• Develop and maintain analytics solutions using Snowflake (Lakehouse, Warehouse, ETL/pipelines, semantic models, and related workloads).
• Integrate and analyze data from multiple sources, including Snowflake, line‑of‑business systems, and cloud platforms.
• Partner with other data engineers and system owners to ensure data structures support accurate and performant reporting.
• Optimize data models and queries for performance, scalability, and cost efficiency.

• Ensure consistency and accuracy of KPIs, metrics, and definitions across reports and dashboards.
• Implement data security practices such as row‑level security (RLS) and appropriate access controls.
• Document data models, reporting logic, and metric definitions to support transparency and maintainability.
• Support data governance and reporting standards across the organization.
• Work closely with business stakeholders to understand reporting needs and drive data‑informed decision‑making.
• Quickly gain sufficient understanding of the business to recognize Analytics needs, gaps in solutions, & processes/stakeholders to involve – independent of significant support.
• Support and enable self‑service analytics while maintaining a trusted, centralized source of truth.
• Provide guidance and best practices for Power BI usage, dashboard design, and analytics workflows.
• Contribute to ongoing analytics and data platform improvements as the organization matures its data capabilities.
• Drive adoption of the reports you produce through trainings, relevance‑iterations, & inserting reports into critical business decision processes.

• Own analytics initiatives from intake through delivery, including requirements prompting & clarification, effort estimation, sequencing work, and managing dependencies.
• Translate business questions into scoped, well‑defined analytical deliverables with clear criteria and metric definitions.
• Plan and execute work to meet agreed‑upon timelines while proactively identifying turnaround risks and trade‑offs.
• Maintain clear communication with stakeholders on progress, blockers, and changes in project plans.
• Estimate cost, effort, and complexity for analytics work to support capacity planning and prioritization.
• Design scalable, efficient data models and pipelines with…