Axios
Analytics Engineer
About this role
Axios seeks an Analytics Engineer to design and maintain curated data layers and dashboards that drive business insights and decision-making. You'll bridge data engineering, science, and business stakeholders by transforming raw data into reliable metrics, semantic models, and compelling visualizations using modern data stack tools.
What you'll do
- Own and maintain the Gold layer of medallion architecture, including business metrics and semantic models
- Build and maintain executive dashboards and visualizations communicating key insights
- Design data marts and semantic layers serving multiple business domains
- Implement data quality tests, documentation, and lineage tracking for analytics trust
- Collaborate with data engineering and science teams to ensure alignment on data needs and outputs
- Serve as a strategic partner rotating through intake, quality assurance, and domain consulting
What they're looking for
- 2-5+ years analytics engineering, BI development, or data visualization experience
- Advanced SQL proficiency and dbt or similar transformation framework expertise
- BI and visualization tools (Looker, Tableau, Power BI, Mode, or equivalent)
- Modern data warehouse platforms (Snowflake, BigQuery, Redshift, or similar)
- Semantic layer, metric store, and data mart design and modeling
- Medallion architecture and data governance best practices
- Data storytelling and ability to communicate complex concepts clearly
- Versioning, testing, and CI/CD practices for data pipelines
Benefits
- Salary range $130,000–$155,000 based on location and experience
- 401(k) with employer match
- Comprehensive health insurance (PPO and high deductible options) with dental and vision
- Employer HSA contributions
- 12-week paid primary caregiver leave
- Remote-optional work arrangement
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Axios
Axios builds a news delivery platform powered by reliable APIs and services that serve millions of readers daily. The company is hiring backend software engineers and analytics engineers to scale its infrastructure and transform data into actionable business insights.
View all jobs at AxiosLikely interview questions
- Walk us through a time you designed a Gold/curated layer or semantic model. How did you ensure it met business needs and maintained data quality?
- Describe your experience with dbt and SQL in building transformation pipelines. How do you approach testing and documentation to ensure trust in your data models?