Intermediate Analytics Developer

About the opportunity

About VirtasantVirtasant is a global technology services company with a network of over 4,000 technology professionals across 130+ countries. We specialize in cloud architecture, infrastructure, migration, and optimization, helping enterprises scale efficiently while maintaining cost control.Our clients range from Fortune 500 companies to fast-growing startups, relying on us to build high-performance infrastructure, optimize cloud environments, and enable continuous delivery at scale. About the roleOur client develops a powerful AI-powered training and communication SaaS platform that gives frontline workers the knowledge they’re missing to drive measurable business performance.The Intermediate Analytics Developer works at the intersection of data analysis, software development, and AI. You will partner with our client's product and development teams to deliver proactive insights and data products, such as user-facing reports, that enable data-informed decisions. You will also work with AI agents to support intelligent data applications, help automate complex workflows, and surface insights for our client's customers and internal stakeholders. What You’ll Do Build and maintain user-facing reports that help our client's customers understand their workforce and spot opportunities for improvement.Develop and maintain data models and pipelines in Google BigQuery, using techniques like partitioning and clustering to keep reporting fast and cost-effective.Apply statistical techniques to provide meaningful insights and support data-informed decisions.Work with team members - including Product Managers, Developers, Designers, and UX Researchers - to complete feature analyses, respond to ad-hoc data requests, and deliver reports that surface product insights.Review data schemas for new features to ensure they'll support future analytics needs.Provide constructive feedback on PR reviews to support high-quality code delivery.Troubleshoot issues across the analytics stack - from data ingestion through the warehouse and semantic layer - to find the root cause of data discrepancies.Work with AI agent tools within our data applications to support automation and surface insights for customers and internal teams.Contribute to the Data team's shared knowledge base and stay current on emerging practices in analytics and data development. What We’re Looking For Degree in a quantitative field, or equivalent experience.3+ years of experience in data analysis or a similar role.Strong SQL skills, with hands-on experience in BigQuery and Looker.Experience with Python for data tasks such as scripting, data engineering, or pipeline work.Familiarity with Generative AI tools and LLMs for use cases like code generation, data cleaning, or workflow automation.Working knowledge of data warehousing concepts and how they apply to analytics and reporting.Solid foundation in statistics, including techniques like t-tests and linear regression.Ability to communicate clearly about data topics with both technical and non-technical audiences.Good product and business sense; you understand how data connects to what our client's customers need.Experience building and managing projects within BigQuery Analytics Hub is considered a strong asset (but not mandatory).Knowledge of Java is considered a strong asset (but not mandatory). Our recruitment processRecruiter interview (30 min)Tech interview (30 min)Client interview - Hiring manager interview (1 hour)Client interview - Technical interview 1 (1 hour)Client interview - Technical interview 2 (1 hour)Client interview - Executive interview (30 min)We strive to move efficiently from step to step to make the recruitment process as fast as possible.What we offerTotally remote, full-time (40h/week)Work hours - 8 hours a day, East Coast office hoursIndependent contractor agreementPayment in USD, biweekly or monthly - your choice

Responsibilities

• Build and maintain user-facing reports that help our client's customers understand their workforce and spot opportunities for improvement.
• Develop and maintain data models and pipelines in Google BigQuery, using techniques like partitioning and clustering to keep reporting fast and cost-effective.
• Apply statistical techniques to provide meaningful insights and support data-informed decisions.
• Work with team members - including Product Managers, Developers, Designers, and UX Researchers - to complete feature analyses, respond to ad-hoc data requests, and deliver reports that surface product insights.
• Review data schemas for new features to ensure they'll support future analytics needs.
• Provide constructive feedback on PR reviews to support high-quality code delivery.
• Troubleshoot issues across the analytics stack - from data ingestion through the warehouse and semantic layer - to find the root cause of data discrepancies.
• Work with AI agent tools within our data applications to support automation and surface insights for customers and internal teams.