Maintain the semantic layer. Build and maintain Databricks metric views, the data dictionary and model documentation in Unity Catalog, so every certified metric has one definition used everywhere.
Make commercial data AI-ready. Curate the catalog, descriptions and verified queries the AI agent reads over MCP and maintain a revenue regression question set that measures agent accuracy as models change.
Protect data quality. Apply dbt model contracts and tests to certified models. Define freshness, volume and anomaly checks, maintain model lineage and work with the Senior Data Engineer to resolve upstream issues.
Enable predictive analytics. Supply governed revenue, contract and subscription features to machine learning models, alerts and AI agents.
Deliver business-facing analytics. Own GTM and revenue forecasting datasets and BI feeds. Translate stakeholder questions into reusable data products and prioritize work with business partners.
Raise engineering standards. Review dbt code, establish modeling conventions and mentor peers. Use AI-assisted tools for SQL, tests, and documentation while holding generated work to production standards.
What you bring
These are required. We are hiring for depth in modeling and business judgment.
Production modeling. 5+ years building production data models in analytics or data engineering, ideally with a GTM, RevOps or SaaS revenue focus, including at least 3 years in dbt: incremental models, snapshots, macros, tests, documentation and CI with state-based deferred builds.
Strong SQL. Databricks and Delta experience is preferred; Snowflake or BigQuery experience transfers.
Salesforce fluency. Hands-on knowledge of the Salesforce data model, including accounts, opportunities, opportunity line items, contracts, assets or entitlements, quotes and subscriptions, and field history.
SaaS revenue metrics. Able to define and defend ARR and MRR, bookings, renewals, expansion, churn and downsell, net and gross revenue retention, and how double counting happens.
Metric ownership. Documented business definitions, resolved conflicting numbers across teams, and secured stakeholder approval before publishing metrics.
Data quality discipline. Experience with model contracts, reconciliation, testing strategies and freshness or anomaly monitoring for production analytics models.
Engineering discipline. Git, code review, pull requests, CI and promotion through environments, and a habit of validating AI-generated code before it ships.
Clear communication. Able to explain modeling decisions and tradeoffs to non-technical stakeholders and turn ambiguous questions into agreed requirements.
Nice to have
Unity Catalog governance. Governed tags, attribute-based access control (ABAC) column masks, and lineage.
CI/CD for Databricks. Declarative Automation Bundles and Git-based deployment workflows.
Semantic layers. dbt Semantic Layer (MetricFlow), Cube, Looker (LookML), or Databricks metric views.
Agent-facing data tools. MCP servers, verified queries, and agent evaluation datasets.
Feature engineering. Model-ready features for churn or propensity models.
BI and dashboards. Power BI or Databricks AI/BI dashboards.
Application Process
If you thrive in a fast paced environment and you are eager to make a significant impact in the field of accessibility, we would love to hear from you! Interested in immediate consideration? Please submit your resume to be considered for this role. The anticipated application window is 40 days from the date job is posted. However, factors such as candidate flow and business necessity may require us to shorten or extend the application window. This position is a current open vacancy. Candidates who are selected for an interview will be notified of the hiring decision within 45 days following their final interview. Level Access is committed to workforce diversity and is an Equal Opportunity Employer. We are dedicated to providing reasonable accommodations throughout the hiring process. Level Access uses artificial intelligence (AI) tools to support and enhance our recruitment and hiring processes. These tools may assist with activities such as résumé screening, skills assessments, interview scheduling, and communication These tools are designed to assist our recruiters and do not make final hiring decisions. All AI-assisted processes are subject to human review and candidate information is handled in accordance with our Privacy Policy and applicable regulations. To learn more about how we collect and use personal data, please review our Privacy Statement (https://www.levelaccess.com/privacy-statement) and our Trust Center (https://trust.levelaccess.com).
Compensation and Benefits
This is a full time position. The annual base salary hiring range for this position is $92,000 - $100,000 for employees located in the United States and CA$86,000 - CA$130,000 for employees located in Canada. The salary range reflects expected base pay for this role at the time of posting. The compensation package offered will be determined by factors such as demonstrated experience, skills, and internal equity. Expected base pay hiring ranges for candidates outside of the United States and Canada will be reviewed during the interview process, if selected. This position is eligible for incentive compensation in the form of a company bonus plan. Level Access is committed to supporting our global team with comprehensive and inclusive benefits. For employees in the United States and Canada, our offerings include medical, dental, and vision insurance, life and disability coverage (STD/LTD), and a retirement match. We also prioritize well-being and growth through flexible paid time off, paid parental leave, a remote work stipend, and professional development reimbursement. For employees in other locations, benefits are tailored to local regulations and employment status to ensure competitive support worldwide.
