Location: Dallas, TX

The Data Analyst is responsible for building and maintaining analytics solutions that drive product and business decisions across the organization. This role involves querying and transforming data in Databricks, developing interactive dashboards in Power BI, contributing to the semantic layer for consistent metric definitions, and supporting data pipeline reliability. The analyst partners with product, engineering, and go-to-market teams to deliver self-service analytics, surface actionable insights from SaaS metrics, and ensure data quality across key reporting surfaces.

Responsibilities
• Databricks Analytics: Write and optimize SQL and Python queries in Databricks to extract, transform, and analyze large-scale product and business data sets for stakeholder consumption.
• Power BI Dashboard Development: Design, build, and maintain Power BI reports and dashboards that surface SaaS KPIs such as ARR, churn, NRR, and product adoption metrics for cross-functional teams.
• Semantic Layer Contribution: Support the development and maintenance of the enterprise semantic layer to ensure consistent metric definitions, business logic, and governed data access across reporting tools.
• Cross-Functional Analytics Support: Partner with product, engineering, finance, and GTM teams to scope analytical requests, deliver ad-hoc analyses, and translate findings into actionable recommendations.
• Data Quality and Pipeline Support: Monitor data freshness and accuracy, troubleshoot pipeline issues in collaboration with data engineering, and ensure reporting surfaces reflect trusted, governed data.

Scope/Key Deliverables
• Power BI Dashboards and Reports: Production-quality dashboards covering SaaS KPIs (ARR, churn, NRR, feature adoption) with documented data sources and refresh schedules.
• Databricks Notebooks and Queries: Documented, version-controlled SQL/Python notebooks for recurring analyses, cohort studies, and ad-hoc deep-dives supporting product and GTM stakeholders.
• Semantic Layer Contributions: Validated metric definitions, dimension models, and business logic additions to the shared semantic layer, ensuring consistency across self-service analytics.

Qualifications
• Databricks and SQL Proficiency: Strong hands-on skills in Databricks (Spark SQL, notebooks, Delta Lake) and advanced SQL for data transformation, analysis, and pipeline support. Familiarity with Power BI (DAX, data modeling, service administration) for dashboard development and self-service enablement.
• Semantic Layer and Data Modeling: Understanding of semantic layer concepts, dimensional modeling, and metric frameworks to ensure consistent, governed definitions across reporting tools. Exposure to AI/BI features (e.g., Databricks AI/BI dashboards, Genie spaces) is a plus.
• Analytical Communication: Ability to translate complex data findings into clear, stakeholder-ready narratives and visualizations. Comfortable presenting to product, engineering, and business audiences and partnering across teams to scope and deliver analytical work.

Education & Experience
• Education: Bachelor's degree in Data Analytics, Computer Science, Information Systems, Statistics, or a related quantitative field.
• Experience: 2-4 years of professional experience in a data analyst or analytics engineering role, ideally within a SaaS or technology company. Hands-on experience with Databricks and Power BI required. Exposure to semantic layer tooling, AI/BI enablement features, or data governance frameworks is preferred.

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