Primary Duties
- 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.
- 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.
- 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).
Minimum Qualifications
- 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.
Preferred KSA's
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.
Experience building full stack web applications and beautiful UIs to surface data insights.
Proficiency in applying GenAI tools to streamline both data engineering and frontend app development.
Experience in designing, building and optimizing data pipelines and ETL processes.
Experience building continuous integration and continuous deployment (CI/CD) pipelines.
Experience with security and systems that handle sensitive data.
Domain Specific Experience
Full Stack:
Data Infrastructure:
Physical Requirements
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