Senior Associate, Business Intelligence Engineering

Core Spaces•UNAVAILABLE, UNAVAILABLE

11d

About The Position

Core Spaces is seeking a Senior Associate, Business Intelligence Engineering to own the reporting and analytics solutions that power decision-making across the business, translating complex data needs into scalable, trusted, and actionable insights. The Senior Associate is responsible for designing, building, and maintaining the semantic models, data models, data pipelines, and Power BI solutions that support decision-making across Finance, People Operations, Student Housing, Build-to-Rent, Construction, Marketing, and Investments. Working across a diverse technology landscape, the Senior Associate must navigate varying source systems, data structures, business definitions, and reporting requirements to deliver consistent and reliable analytics solutions across the business. Core's analytics platform is built on Azure, Databricks, Delta Lake, Unity Catalog, and Power BI, and this role plays a critical part in developing the data foundation that powers business reporting. The Senior Associate will evaluate reporting requirements beyond the dashboard layer, identifying when new measures, business logic, data structures, or source system integrations are needed. Rather than relying on report-level workarounds, this individual is expected to architect and implement sustainable solutions that address challenges at the source while balancing strong technical expertise with a practical understanding of business needs.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field; or equivalent combination of education and professional experience.
3 or more years of hands-on experience developing production business intelligence and analytics solutions, including significant ownership of Power BI semantic models, data modeling, performance optimization, deployment practices, and production support.
Advanced proficiency in Power BI, DAX, and Power Query (M), including filter context, context transition, time intelligence, measure branching, calculation groups, row-level security, and measure performance tuning.
Deep dimensional modeling experience, including star schema design, grain selection, conformed dimensions, slowly changing dimensions, fact table design, relationship strategy, model refactoring, and the ability to design models that scale across multiple reporting use cases.
Strong SQL development skills, including window functions, common table expressions, complex joins, query tuning, reconciliation logic, and development against large and complex fact tables.
Working proficiency in PySpark or Python for data transformation, pipeline development, automation, and troubleshooting within a modern cloud data platform.
Hands-on experience with a modern lakehouse or cloud data platform, ideally Databricks with Delta Lake and Unity Catalog, including an understanding of governed data access, catalog structure, and production data management practices.
Experience designing, building, maintaining, and troubleshooting orchestrated data pipelines using Databricks Workflows, Delta Live Tables, Azure Data Factory, or equivalent tooling.
Demonstrated ability to translate designs, mockups, specifications, and business outcomes into scalable technical solutions, including identifying missing data, ambiguous logic, modeling gaps, and downstream dependencies before development begins.
Demonstrated ability to work independently with limited day-to-day direction, exercise sound technical judgment, prioritize competing work, communicate tradeoffs, and make recommendations that account for accuracy, maintainability, scalability, and business impact.
Strong attention to detail and a demonstrated commitment to data accuracy, particularly for reporting used in financial, operational, executive, or compliance-sensitive decision-making.

Nice To Haves

Databricks with Unity Catalog, Delta Lake, and Delta Live Tables.
Microsoft Fabric, including Lakehouse architecture, Direct Lake semantic models, and capacity management.
Student housing, build-to-rent, multi-family, real estate, or PropTech data, ideally supporting a vertically integrated owner and operator.
Property management, ERP, HRIS, or construction management platforms and their underlying data structures, such as Entrata, Yardi, RealPage, Workday, or Procore.
Revenue management, pricing, or forecasting analytics, including pre-lease pace, net effective rent, and absorption reporting.
Working within an Agile delivery process alongside Product Management, including Azure DevOps boards, sprint planning, and backlog refinement.
Data quality testing frameworks and data pipeline observability practices.

Responsibilities

Own the end-to-end technical delivery of production Power BI reports and dashboards from approved mockups, wireframes, and specifications, ensuring final solutions accurately reflect design intent while meeting standards for usability, performance, governance, accessibility, and long-term maintainability.
Serve as a senior technical owner of the Power BI semantic layer, including star schema data models, reusable DAX measure libraries, calculation groups, incremental refresh configuration, row-level security, certification standards, and ongoing model stewardship.
Partner with Product Management before development begins to validate technical feasibility, confirm data availability, surface design gaps or ambiguities, assess performance implications, estimate level of effort, and recommend implementation tradeoffs that balance speed, accuracy, scalability, and business value.
Determine the upstream data, modeling approach, and pipeline logic required to support reporting outcomes, including situations where a needed measure, dimension, attribute, relationship, history, or grain does not currently exist in the data platform.
Translate dashboard intent into the correct Power BI implementation, including visual selection, page structure, drill-through paths, bookmarks, cross-filtering behavior, slicer and parameter configuration, tooltip design, navigation, and user experience patterns appropriate for executive, operational, and analytical audiences.
Design, develop, and maintain data ingestion and transformation pipelines using Spark SQL, PySpark, Delta Live Tables, and Databricks Workflows, ensuring pipelines are reliable, documented, observable, and aligned with enterprise data architecture standards.
Onboard new source systems into the data platform as additional business functions come into reporting scope, including evaluating source data structures, defining ingestion patterns, mapping business entities, establishing refresh cadence, and coordinating validation with the appropriate stakeholders.
Implement complex business logic and measure calculations in DAX consistent with business definitions established through Product Management, documenting assumptions, calculation methodology, dependencies, limitations, and downstream reporting impact.
Investigate, diagnose, and resolve data quality, data integrity, reconciliation, and performance issues at the appropriate source layer, partnering with data architecture, engineering, product, and business stakeholders as needed to prevent recurring issues.
Validate reported figures against applicable systems of record before release, including reconciling key metrics, documenting exceptions, escalating unresolved discrepancies, and ensuring reporting outputs can be trusted for financial and operational decision-making.
Optimize report, semantic model, and pipeline performance through query tuning, aggregation strategy, storage mode selection, model size management, refresh duration analysis, partitioning strategy, and effective use of Power BI and Databricks capabilities.
Manage the Power BI delivery lifecycle across development, testing, deployment, and production support, including workspace and app structure, deployment pipelines, promotion across environments, refresh monitoring, failure remediation, gateway configuration, access management, and release readiness.
Operate independently across concurrent reporting and data engineering initiatives, proactively communicating status, risks, dependencies, tradeoffs, and recommended next steps to Product Management, Data and Analytics leadership, and business stakeholders.
Contribute to documentation, technical standards, reusable patterns, and knowledge sharing that improves team efficiency and supports consistent reporting practices as Core’s analytics environment scales.
Occasional travel may be necessary as needed.
Perform all other duties and tasks as assigned by management.
Must be able to complete all physical requirements of this role with or without a reasonable accommodation.

Benefits

A culture that provides you with a sense of belonging
Competitive pay that values your contributions
Incentives designed to reward your achievements
Paid flexible PTO to disconnect or celebrate life milestones
Paid 14+ holidays, including your birthday, to disconnect and celebrate
Paid Parental Leave that begins after 90 days
Paid volunteer time off to give back to your community
Monthly workshop weeks; fewer meetings & more collaboration
Robust health plan options that begin within at least 30 days of your employment
Monthly phone reimbursement
Wellness allowance and perks, including a yearly subscription to a meditation app
An environment that provides you a voice to share your perspectives
Employee Assistance Program (EAP) for access to confidential support services
Company retirement options including 401(k) + matching & Roth account option