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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Analytics Engineer - **Company:** Axios - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $130,000.0 - $155,000.0 - **Contract:** Permanent contract - **Skills:** Data Analysis, Business Intelligence Development, BigQuery, Continuous Integration, Information Engineering, Data Mart, Data Presentation, Data Visualization, Data Warehousing, Power BI, SQL Databases, Tableau (Software), Management of Software Versions, Snowflake, Data Layers, Looker Analytics, Data Pipelines, Amazon Redshift - **Published:** August 1, 2026 - **Apply:** https://www.workingnomads.com/job/go/1766258/ ## About the Role * 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. ## Description 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. Responsibilities: * Own the Silver and Gold layers 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., * 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [REST, GraphQL, gRPC, and more: A comparison of modern API styles](https://www.wearedevelopers.com/videos/100247-rest-graphql-grpc-and-more-a-comparison-of-modern-api-styles) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Making Data Warehouses fast. 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