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easypayfinance

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Lead Analytics Engineer

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Summary

Lead Analytics Engineer owning a consumer lender's SQL Server analytics database end to end: ingesting data from vendor APIs (CRM, contact center, lending platforms), modeling trusted tables, running scheduled jobs, delivering operational reporting, and governing KPI definitions while leading one analyst. Core stack: SQL Server, Python, Git, and BI tools.

POSITION OVERVIEW

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.

KEY RESPONSIBILITIES

  • 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.

REQUIRED QUALIFICATIONS

  • 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.

PREFERED QUALIFICATIONS

  • 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.

YOUR FIRST 90 DAYS

  • Learn the business and the current platform.
  • 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.

WHAT WE OFFER

  • Compensation is based on work location.
    San Diego (onsite/hybrid): $150,000–$180,000 base per year.
    Remote (outside California): $135k-$160k base per year, set by the labor market for the candidate's location. *
    Individual offers within each range depend on job-related factors such as experience, skills, and qualifications.
  • Relax and recharge with Paid Time Off (PTO) Program; plus 10 paid holidays
  • Financial health with 401(k) programs and employer match
  • Internet reimbursement - $40 per month
  • Take care of your emotional, physical, and financial wellbeing with access to EAP
  • We invest in your future through ongoing learning and development resources
  • Save on taxes with Flexible Spending or Health Savings Accounts
  • Peace of mind with Life and AD&D Insurance
  • Discounts for shopping at various retailers

Skills

What Lead Data Analytics jobs ask for — and how much of it you have →

See also

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