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# Lead Analytics Engineer

- **Company:** EasyPay Finance
- **Location:** Vista, CA, United States
- **Experience:** Expert
- **Salary:** $135,000.0 - $180,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Databases, Data Dictionary, Python (Programming Language), Microsoft SQL Server, SQL Azure, Operational Databases, Raw Data, Salesforce.Com, Tableau (Software), Data Logging, Genesys, Large Language Models, Git
- **Published:** September 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=5afa7fed87274421

## About the Role

* 5+ years running production data pipelines and reporting.
 * Strong SQL Server: window functions, dedup, and performance on big tables.
 * Python and API extraction and pipelines.
 * Experience operating scheduled jobs and logging, alerting, and quality checks.
 * You've published data to a BI tool and supported the people using it.
 * Comfortable working in Git., * Consumer lending or financial services experience.
 * Salesforce or Genesys Cloud Data
 * Tableau, Metabase, ThoughtSpot, Omni, or similar
 * dbt, AZURE SQL, or AI/LLM tooling on data.

## Description

We're consolidating analytics onto a single SQL Server database that sits right alongside our lending systems, and you'll own it end to end: what lands in it, how it's modeled, and the reporting that runs off it. The goal is self-service - governed tables, a real data dictionary, and published models so that most questions answer themselves. When someone does need you directly, the result should be a reusable asset, not a one-off number.

This is a hands-on job for someone who likes to finish things and keep them running. You'll inherit a working platform and a team that has already solved the hard migration problems. From there, the work is new sources, shared definitions, better distribution, and a roadmap you help write., * Run the analytics database and its scheduled jobs - reliable, monitored, and documented.

 * Pull in new sources through vendor APIs (CRM, contact center, lending platforms) with incremental, restartable laods
 * Model raw data into tables and views the business can trust.
 * Build operational reporting that has to be right every day: call lists, merchant partner reporting, and management reports.
 * Own the data dictionary and KPI definitions in partnership with business owners.
 * Lead one analyst, setting direction and raising the bar on quality., * Operate - take over daily operations of the platform alongside the team.
 * Deliver - land one new source, end to end.
 * Define - get the first shared KPI definitions agreed and written down.


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