Data Analyst

Title: Data Analyst, Advisory Data & Research
Location: Richardson TX (Hybrid: M-F 8am-5pm)
Duration: 6 Months - C2H


Resource's typical working day:
Collaborating with product managers and engineers and the greater team
Large amounts of data analysis
Giving daily/weekly updates to executive team
Linking incoming data to a source of truth


Must Have Skills:
Must be proficient in using AI
Experience with commercial real estate data
Able to present and communicate ideas to C-suite executives


Nice to have skills:
Able to think critically and ask questions for clarification


Soft Skills:
Need to be able to think strategically


Years of Experience: 3-5+ years


Education:
Bachelor's degree strongly preferred, but extra experience will be considered


Software skills:
Proficiency with Microsoft Office tools (Word, Excel, Outlook, PowerPoint) and familiarity with modern analytics and data warehousing platforms (e.g., Snowflake, Databricks)


Interview Process:
1st round virtual with H.M. 2nd round with team


This isn't a reporting-factory role. You'll help frame the questions and define the methodology. You will drive the analysis, and be accountable for the insights. You'll partner with UX designers and product managers to embed analytics people actually use, push engineering teams on data quality and pipeline reliability, and represent your findings to business leaders and D&T leadership alike.
What You'll Do
* Own analytical workstreams end-to-end - synthesize input from users, business stakeholders, and D&T leadership into a clear, prioritized set of questions to answer and metrics to track.
* Build, maintain, and refine dashboards, reports, and self-service analytics: write clean, well-documented SQL, groom data backlogs, lead refinement sessions with stakeholders, and actively participate in scrum ceremonies, demos, and lead user testing and rollout of analytical products.
* Drive data discovery alongside Product and UX partners - conduct user research on analytical needs, run feedback sessions, and champion the end-user perspective in every metric and visualization decision.
* Translate business questions into execution by collaborating closely with Engineering and Data Engineering, turning analytical requirements into well-modeled, reliable, queryable data.
* Define and deliver specific analyses end-to-end, from problem framing through validation, presentation, and measurement of impact.
* Represent your analysis to business leadership and D&T leadership - providing crisp, regular readouts and connecting day-to-day work to broader strategic goals.
* Spot data quality problems before they become blockers: proactively investigate anomalies, resolve issues, and communicate with clarity and urgency when it matters.
* Model client's RISE values on your team and in every cross-functional interaction - lead by example, build trust fast, and bring people along.
What You'll Need
* 3-5+ years of experience in Data Analytics, Business Intelligence, Business Analytics, or a related quantitative field - with a track record of delivering analyses that influenced decisions. A bachelor's degree in a quantitative discipline is preferred; relevant experience counts.
* Strong SQL skills with hands-on experience querying large, complex datasets, plus fluency building dashboards and reports in modern BI tools (Power BI, Tableau, Looker, or similar). Proficiency in Python or R for analysis and automation is a plus.
* Strong instincts for prioritization - you know which questions matter, and you know how to explain why.
* The communication skills to work across levels: from a debugging session with a data engineer to a C-suite readout, you adjust your style and land your message.
* A bias for the truth - you ask hard questions of the data, validate your assumptions, and let what you find change your mind.
* Comfort navigating ambiguity, managing competing priorities, and keeping work focused when requirements shift.
* Proficiency with Microsoft Office tools (Word, Excel, Outlook, PowerPoint) and familiarity with modern analytics and data warehousing platforms (e.g., Snowflake, Databricks).
* Experience with data modeling, data quality, and data governance - you understand data and how it interacts with products and decisions.
* Experience in Commercial Real Estate (nice to have).