Analytics Engineer
Description For Analytics Engineer
HUMAN Security's Data & Analytics team is seeking an Analytics Engineer to strengthen their data infrastructure capabilities. This role is crucial in processing over 40T+ decisions weekly across their platform. As an Analytics Engineer, you'll be the bridge between Engineering, Data Analysts, and Operational teams, ensuring reliable, analytics-ready data throughout the organization. The position focuses on managing ETL processes, building and maintaining infrastructure, and improving cost management systems. You'll work with modern data stack technologies, handling large-scale datasets, and collaborate with Finance and FinOps teams. The ideal candidate should have strong SQL and Python skills, experience with modern data tools, and understanding of cloud infrastructure costs. This role offers an opportunity to impact business decisions through data-driven insights while working in a dynamic, cross-functional environment.
Responsibilities For Analytics Engineer
- Manage ETL processes from disparate systems to centralize data in analytic warehouse
- Design, build, and maintain infrastructure for Data & Analytics team
- Build analytic ready data sets using data modeling best practices
- Partner with technical functions in Engineering for alignment on tooling, infrastructure, and processes
- Manage cost and efficiencies of pipelines and queries
- Improve understanding of cost data for gross margin, contract management, and infrastructure spend
- Build pipelines and data sets for Finance and FinOps teams to manage cost data
Requirements For Analytics Engineer
- Excellent SQL skills (window functions, subqueries, CTEs, temp functions)
- Proficient in Python, R, and/or dbt
- Ability to work cross-functionally with senior technical and non-technical team-members
- Experience managing modern data stack (dbt, Fivetran, Snowflake, Gitlab, Docker, Looker)
- Experience managing large data sets (1B+ rows)
- Familiarity with cloud infrastructure costs (Snowflake, GCP, AWS) and financial metrics
- Comfortable working in an agile environment
- 2 - 4 years of relevant experience in analytics and/or analytics engineering
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