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Salary: USD 165,000 - 195,000 / annual
Extend is a B2B SaaS platform that powers post-purchase experiences for retailers through AI-driven solutions including automated customer service, returns/exchange management, fulfillment automation, and fraud detection. The company works with over 1,000 merchant partners and is backed by prominent technology investors with headquarters in San Francisco.
You will lead the Analytics Engineering team, which owns the data platform that powers all analytics, actuarial modeling, risk analysis, fraud detection, product analytics, and financial reporting across the company. This team manages the Snowflake data warehouse, dbt repository, data ingestion pipelines, and monitoring infrastructure that serves Analytics, Actuarial, Risk, Fraud, Product, Operations, Finance, Accounting, and Revenue teams.
Key responsibilities include:
- Managing and growing a remote team of analytics and data engineers through hiring, onboarding, career development, and performance management
- Setting technical standards and owning the dbt repository as a shared platform, including PR review, architecture decisions, testing, documentation, and CI standards
- Owning the Snowflake warehouse, dbt execution, source ingestion, freshness monitoring, external tables, and AWS Glue/CDK jobs
- Modeling core business domains (orders, contracts, claims, service orders) to ensure consistency across the organization
- Leading platform migrations and retiring legacy components on a planned timeline
- Building trusted relationships with internal stakeholders by translating business questions into data models and aligning on shared definitions
- Hardening data quality through schema validation, freshness audits, and critical-service monitoring
- Running platform operations including on-call, monitoring, alerting, incident triage, and root-cause analysis
- Enabling self-service analytics through documentation, semantic consistency, and BI access
- Automating operational workflows using AI-assisted tools for alert triage, refresh requests, and file processing
Requirements:
- 2+ years managing engineers on a data or analytics engineering team, with demonstrated hiring, performance management, and career development experience. Lead engineers who have owned technical direction and developed engineers around them will be considered.
- Advanced SQL and dimensional modeling experience, with proven ability to model business domains for multiple stakeholders and maintain consistency through changing requirements
- Deep dbt experience, including owning a version-controlled repository with testing, PR review, CI, and change control standards
- Pipeline engineering expertise with Python and cloud data infrastructure (AWS Glue, Step Functions, Lambda, CDK)
- Reliability ownership experience, including on-call management for data platforms, building trusted alerting, and leading incident response
- Experience supporting analysts, data scientists, or quantitative teams and translating business questions into data models
- Clear written communication skills for architecture proposals, incident reviews, and tradeoff summaries
- Strong prioritization judgment across competing requests with clear communication of tradeoffs
- Bonus: experience with actuarial, risk, or fraud analytics; warranty, insurance, or service-contract programs; financial and revenue reporting; privacy and deletion compliance at scale; BI administration; or AI-assisted engineering workflows
