Senior Analytics Engineer

The big picture: Axios is a media company dedicated to delivering trustworthy news and information with efficiency, clarity, and Smart Brevity. As a Senior Analytics Engineer at Axios, you’ll combine engineering rigor, business context, and storytelling to transform complex data into clear, consistent, and actionable insights. You’ll design, maintain, and evolve the curated layers of our data platform ensuring data is reliable, modeled for clarity, and accessible to everyone—from product partners to executives.

Why it matters: In partnership with data engineers, data scientists, and product managers, you’ll transform raw and complex source data into well-structured data products, certified dashboards, and compelling visualizations that underpin reporting, experimentation, and advanced analytics. You’ll also play a key role in developing a self‑service analytics platform, ensuring that models and data structures empower teams across Axios to independently explore data, generate insights, and make confident, data‑informed decisions.

• Own the gold and silver layers of the medallion architecture: define, version, and maintain business metrics and semantic models and data glossaries.
• Partner with data engineering to shape the silver layer, ensuring upstream data is complete, performant, and aligned with business needs.
• Build and maintain executive dashboards and visualizations that communicate key insights effectively.
• Define and enforce best practices for analytics modeling, data documentation, and visualization standards.
• Design and maintain data marts, metric stores, and semantic layers that enable consistent reporting across teams.
• Ensure dashboards and data models are accurate, documented, and certified for stakeholder trust.
• Partner with data scientists and ML Ops to document and integrate model outputs into analytical workflows.
• Lead initiatives to improve data quality, observability, governance, and glossary management across analytics workflows, ensuring strong, business‑aligned definitions that prevent metric drift and maintain consistency over time.
• Mentor mid‑level analytics engineers, helping them strengthen technical, communication, and stakeholder management skills.
• Act as a trusted advisor to product, business, and editorial leaders, ensuring analytics aligns with company priorities and drives impact.
• Ensure that analytics modeling and data structures are designed to power a self‑service platform, enabling teams across Axios to explore reliable data, access well‑defined metrics, and derive insights independently.

• 5‑8+ years in analytics engineering, BI development, or data visualization roles.
• Expert‑level SQL and proficiency in transformation frameworks like dbt.
• Deep experience with BI and visualization tools (Looker, Sigma, or similar).
• Skilled at architecting curated datasets, semantic layers, and metric stores for consistency and scalability.
• Familiar with modern data stack technologies (Snowflake, Big Query, Redshift, or equivalent).
• Strong understanding of medallion architecture, data modeling, and data governance best practices.
• Familiarity with version control, testing, and CI/CD practices for analytics pipelines.
• Excellent communication and data storytelling skills—able to translate technical work into clear, strategic insights.
• Proven ability to influence technical and non‑technical stakeholders and drive adoption of analytics frameworks.

• Business stakeholders rely on your models, dashboards, and semantic layers as trusted sources of truth.
• Data across Axios is consistent, documented, and easily understood by teams.
• Executive dashboards provide clear, actionable insights that guide company strategy.
• Mid‑level analytics engineers grow under your mentorship and adopt your best practices.
• Data engineers and scientists use your frameworks and documentation as foundations for collaboration.
• Leadership views analytics engineering as a strategic enabler of efficiency, clarity, and alignment across Axios.
• You play a critical role in scaling the analytics practice—establishing modeling standards, mentoring peers, and ensuring that dashboards and metrics…