Senior Manager, Senior Analytics Engineer

Description

POSITION DESCRIPTION: 

RESPONSIBILITIES

• Architect, build, maintain, and document production-grade data models in dbt Core or dbt Cloud, transforming raw source data from Salesforce, Q2, and servicing pipelines into clean, tested, analysis-ready tables and views within Snowflake 
• Own the design and governance of EnFin’s enterprise semantic layer, establishing naming conventions, modeling standards, and documentation practices that ensure the data warehouse serves as the single authoritative source of truth for all business reporting and analysis 
• Build analytics-ready intermediate data layers as needed to support functional areas of the enterprise 
• Design and maintain a comprehensive testing framework including schema tests, data freshness checks, and statistical anomaly detection to ensure data integrity and catch regressions before they reach business users; establish alerting standards and on-call protocols for pipeline failures 

• Serve as the enterprise authority on data definitions, metrics governance, and analytical tool standards. Own the certified metrics layer in Tableau and Snowflake, ensuring consistent calculation logic and definitional integrity across all reporting surfaces and business units
• Work closely with third party vendors to ensure rapid implementation and adoption of new analytical or AI tools
• Ensure that metric definitions are accessible to non-technical business users and relevant for their business purposes

• Translate business-defined data quality rules into validation logic including data completeness, conformance, sequencing, and referential integrity 
• Run baseline data quality assessments and produce scorecards by domain and field 
• Own and deliver an executive-level data quality observability dashboard, providing real-time transparency into pipeline health, field-level completeness, and data quality SLAs across all critical business domains 
• Investigate data anomalies, trace issues to their source, and coordinate remediation with the technology team 

• Partner with the technology team on enterprise ETL pipelines, understanding field mapping, sync frequencies, and change data capture status for all critical business fields
• Evaluate and implement solutions to solve field history gaps as appropriate
• Own the governance of the Snowflake analytics environment, including schema organization, role-based access controls, object lifecycle policies, and published best practices for analyst-built objects. Partner with the technology team on warehouse cost optimization and compute management 

• Mentor and develop analytics engineers and business intelligence analysts on the team, providing technical direction, code review, and career growth support. Act as a force multiplier by elevating the technical capabilities of the broader BI function
• Drive the analytics engineering practice forward by establishing coding standards, pull request workflows, CI/CD integration for dbt, and documentation expectations that scale as the team grows
• Contribute to hiring and onboarding decisions for analytics engineering roles. Partner with the Director to shape the long-term technical roadmap for the BI and analytics platform

REQUIRED QUALIFICATIONS

•  Bachelor’s degree in a quantitative or technical field; advanced degree a plus. Minimum of 8+ years of professional experience, including 5+ years in analytics engineering, data engineering, or business intelligence, with at least 2+ years in a senior individual contributor or technical lead capacity owning a production data platform.
• Strong SQL proficiency and ability to write, debug, and optimize complex queries.
• Strong Python proficiency and ability to automate data analysis, develop testing scripts, and support data visualization needs.
• Hands-on experience with git or other comparable version control systems.
•  Hands-on experience with Snowflake or a comparable cloud data warehouse, including schema design, query optimization, and role-based access control. Direct experience with dbt (Core or Cloud) required.
• Demonstrated ability to build data pipelines or models that are well-documented, tested, and maintainable by others.
• Strong written and verbal communication skills, including the ability to work comfortably with both technical and non-technical stakeholders.
• Ability to work in a fast-paced, dynamic environment, manage competing priorities, and deliver results under tight timelines. 

PREFERRED QUALIFICATIONS 

• Direct experience with Tableau, including building certified data sources, managing extract schedules, and governing self-service analytics at an enterprise scale
• Domain experience in consumer finance, solar, or fintech with working knowledge of loan origination, underwriting decisioning, or servicing data models
• Experience with Salesforce data architecture, including standard and custom object relationships, reporting snapshots, and strategies for extracting historical data via CDC or batch processes
• Proficiency with AI-assisted development workflows and demonstrated ability to evaluate, pilot, and integrate emerging analytics or AI tooling into a production data environment

The salary range is required by the California Pay Transparency Act and may differ depending on the location of those candidates hired nationwide. Actual compensation is influenced by a wide array of factors including but not limited to, skill set, education, licenses and certifications, essential job duties and requirements, and the necessary experience relative to the job’s minimum qualifications.

*This target salary range is for CA positions only and should not be interpreted as an offer of compensation.

hqca-recruiting@qcells.com