Analytics Engineer, Corporate Reporting (US)

Logos is a purpose-driven tech company dedicated to building technology solutions that equip the Church to grow in the light of the Bible. They are seeking an Analytics Engineer to own corporate reporting models and dashboards, ensuring data quality and supporting advanced analysis as the role matures. This position involves collaboration with various teams to enhance corporate reporting standards and drive business insights.

Responsibilities:

• Corporate metrics + modeling (dbt + Databricks)Build and maintain dbt models (marts and intermediate layers) in Databricks that power corporate reporting.Translate business requirements into clear model design: grain, conformed dimensions, and scalable KPI logic.Create and maintain strong documentation in dbt (descriptions, lineage, and model intent) so others can build on your work
• Executive dashboards + semantic model ownership (Power BI)Own the Power BI semantic model and the dashboards used by senior leaders and functional teams.Build and maintain DAX measures that are consistent, performant, and aligned to agreed definitions.Ensure dashboards are “executive-ready”: intuitive navigation, trustworthy totals, and clear drill-down paths
• Data quality + operational excellence (Elementary)Implement and maintain Elementary tests and monitoring for freshness, volume, schema changes, and key metric integrity.Investigate discrepancies and incidents (“numbers don’t match”, refresh failures, pipeline changes) and drive resolution.Improve reliability through automation, documentation, and repeatable runbooks
• Analytics that matures toward data science (SQL + Python)Use SQL and Python to answer business questions beyond dashboards: segmentation, cohorts, funnel analysis, churn drivers, onboarding performance, and product usage patterns.Create repeatable analysis patterns (not just one-off notebooks): reusable queries, vetted datasets, and documented methods.Over time, contribute to more advanced work such as forecasting, propensity/risk scoring, and experimentation support where it’s practical and valuable
• Cross-functional partnership and clarityCollaborate with Finance, Product, Marketing, Sales Ops, and Engineering to reconcile definitions and edge cases.Communicate tradeoffs clearly: what’s known, what’s assumed, and what needs follow-up in source systems or upstream pipelines.Help establish and reinforce standards for corporate reporting so teams can move faster with less confusion

Requirements:

• Strong experience with SQL (complex joins, window functions, performance tuning, and debugging)
• Strong experience with Python for analysis (data wrangling, validation, notebooks, basic modeling workflows)
• Hands-on experience with Databricks (Delta tables, notebooks/jobs, working with large datasets)
• Experience building and maintaining Power BI dashboards and semantic models (DAX, modeling, performance)
• Comfort owning production-grade reporting: reliability, stakeholder expectations, and ongoing iteration
• Familiarity with Elementary (or equivalent data observability/testing tools)
• Statistics foundation (confidence intervals, sampling bias, regression basics, experimentation literacy)
• Experience with SaaS metrics (retention, churn, ARR/MRR, cohorts, conversion funnels)
• Experience operationalizing analysis (scheduled outputs, monitored metrics, version control, basic CI practices)