Full-Stack Analytics Engineer II

You will be the hands-on owner of our analytics and data ecosystem, transforming complex data into actionable insights that drive strategic decision-making. In this role, you will manage, build, maintain, and ingest data from various source systems (such as HRIS, ATS, and Identity). We are looking for an ambidextrous engineer who is highly proficient in using Claude Code and other GenAI tools to rapidly build both the middle data layer (canonical models, semantic layers) and the app layer. Through this hybrid approach, you will surface insights and create beautiful UI visuals that translate complex data into clear, compelling narratives for end users.

1. Data Ingestion & Modeling (40%): Partner with Data Platform/IT to ingest data from diverse source systems; own the "T" in ELT using dbt, implementing tests, lineage, and data contracts.
2. Full-Stack & GenAI Development (40%): Leverage Claude Code and other GenAI tools to build the middle data layer and app layer, creating interactive dashboards and beautiful UI visuals that go beyond traditional reporting to surface insights.
3. Analytics & Strategy (20%): Analyze complex datasets to identify trends and perform root cause analysis, collaborating with cross-functional leaders to iterate key performance indicators while implementing strict privacy-by-design (PII minimization, RBAC).

3+ years of experience as an Analytics Engineer, Data Engineer, or in a related field delivering production-grade data models and durable data products.

Expert SQL skills; deep experience with dbt and dimensional/event-temporal modeling.

Demonstrated ambidexterity in using Claude Code and other generative AI tools to accelerate full-stack development, data modeling, and UI creation.

Hands-on experience with a cloud warehouse (Snowflake/BigQuery) and an orchestrator (Dagster/Prefect/Airflow).

Proficient in Python or R for data transformations, statistical analysis, and automation.

Strong communication skills with a track record of translating complex analytical findings into actionable business insights.

• Advanced degree in Statistics, Data Science, Psychology, Economics, or related quantitative field.

• Track record integrating HRIS/ATS/payroll/identity sources and hardening metrics for exec-level decisions.

• Familiarity with data privacy regulations (GDPR/CCPA) and ethical considerations in analytics.