Analytics Engineer

1 big thing: Axios is a growth-focused media company dedicated to helping people get smarter, faster on what matters. As we continue to scale, data plays a critical role in how we drive that mission forward. Why it matters: As an Analytics Engineer at Axios, you’ll serve as the primary interface for delivering insights to the business. You’ll design and maintain the curated layers of our data platform (Silver and Gold), and also own the dashboards and visualizations that translate those data products into actionable insights. By combining engineering rigor with business context and storytelling, you’ll ensure decision-making is faster, clearer, and aligned with Axios’ mission. 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. Starting salary for this role is in the range of $130,000 - $155,000 and is dependent on numerous factors, including but not limited to location, work experience, and skills. This range does not include other compensation benefits. Axios' compensation philosophy takes into account the cost of labor differentials across the country. Because this is a remote‑optional job posting, this salary range takes into account all possible locations within the United States, but candidates will only be eligible for the salary range for their location. Responsibilities Own the Gold layer of the medallion architecture: define, version, and maintain business metrics and semantic models. Build and maintain executive dashboards and visualizations that communicate key insights effectively. Define and enforce best practices for data visualization, storytelling, and stakeholder adoption. Build and maintain data marts and semantic layers that serve multiple domains across Axios. Review and certify dashboards for accuracy, consistency, and adherence to standards. Collaborate with data engineering to ensure Silver layer tables meet business needs. Implement data quality tests, documentation, and lineage tracking to ensure trust in analytics outputs. Serve as a bridge to data science, ensuring feature stores and model outputs are well‑documented and reusable. Contribute to the hub‑and‑spoke model: rotate through responsibilities such as intake, quality assurance, and participation in the analytics hub, while serving as a strategic partner to stakeholders, helping them shape the right questions and identify the decisions their data should inform. Skills 2‑5+ years of experience in analytics engineering, BI development, or data visualization roles. Strong proficiency in SQL and experience with dbt or similar transformation frameworks. Expertise in BI and visualization tools (Looker, Tableau, Power BI, Mode, etc.). Familiarity with modern data stack (Snowflake, BigQuery, Redshift, or equivalent). Experience designing and modeling curated datasets, semantic layers or metric stores, and data marts that drive consistent and reliable decisions. Understanding of medallion architecture and data governance best practices. Solid grasp of versioning, testing, and CI/CD practices for data pipelines. Strong data storytelling and presentation skills; ability to communicate complex concepts clearly. Comfort working in a hub‑and‑spoke model, balancing central standards with domain‑specific consulting. What Success Looks Like Business users rely on analytics engineers for both accurate data models and clear, actionable dashboards. Stakeholders see insights delivered through compelling visualizations that drive decisions. Data engineers know what to build in Silver because requirements are clearly defined upstream. Data scientists can discover and reuse well‑documented features and model inputs. Leadership sees fewer instances of unreliable or inconsistent dashboards and more decisions influenced by consistent, well‑visualized data. You help establish analytics engineering as the cornerstone of the data‑to‑decisions lifecycle at Axios. Benefits 401(k) with employer match Robust PPO and high‑deductible health insurance options on the Blue Cross Blue Shield network Employer Health Savings Account (HSA) contribution for the high‑deductible health plan option Dental and vision coverage Primary caregiver 12‑week paid leave Birth‑givers will have an additional 6‑8 weeks depending on type of delivery, for a total of 18‑20 weeks continuous leave Annual learning and development stipend $100 monthly work‑from‑home stipend Tele‑mental health services through Headspace OneMedical membership, including tele‑health services Personal health advocacy resources through HealthAdvocate Inclusive fertility, hormonal health and family forming benefits through Carrot Fertility Access to the Axios “Family Fund”, which was created to allow employees to request financial support when facing financial hardship or emergencies Increased work flexibility for parents and caretakers Virtual company‑sponsored social events A strong and positive work environment A commitment to an open, inclusive, and diverse work culture Equal Opportunity Employer Statement Axios is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, age, gender identity, gender expression, veteran status, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, and local laws. This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. Axios makes hiring decisions based solely on qualifications, merit, and business needs at the time. #J-18808-Ljbffr Axios