Analytics Engineer

Key Responsibilities

• Understand stakeholder data needs across Ops, Finance, and the GTM org (Sales, Marketing, BDR, Customer Success) and translate them into technical requirements
• Define, build, and manage key data pipelines in dbt that transform raw data into canonical datasets
• Use AI tools, LLMs, and agents to accelerate analytics workflows including data exploration, pipeline development, QA, documentation, dashboard creation, and stakeholder enablement
• Read, write, debug, and validate SQL, Python, dbt models, and AI-generated code to ensure outputs are accurate, reliable, and production-ready
• Establish high data integrity standards, SLAs, and QA processes for timely and accurate data delivery
• Develop reliable dashboards to track core business, GTM, and operational metrics
• Build foundational data products, dashboards, automations, and internal tools that enable self-serve analytics
• Bring a strong point of view on build vs. buy decisions across the GTM data stack
• Partner with GTM and Finance leaders to influence roadmap decisions from a data systems and analytics perspective
• Become an expert in Oscilar's data models, business metrics, GTM systems, and broader data architecture
• Help shape a modern, AI-native analytics engineering function

Required Qualifications

• 5+ years of experience as an Analytics Engineer, Data Engineer, or in a similar Data Science & Analytics role
• Experience partnering with GTM, Finance, and cross-functional leaders to build and report on company-wide metrics
• Strong SQL and Python skills, with the ability to transform raw data into clean, accurate, and scalable data models
• Experience building multi-step ETL workflows and robust data models using tools like dbt
• Strong AI fluency, with hands-on experience using tools like Claude, LLMs, and/or AI agents to accelerate technical analytics, data engineering, automation, or reporting workflows
• Ability to use AI-generated code and analysis effectively while independently reviewing, debugging, and validating the underlying logic
• Familiarity with workflow orchestration tools like Airflow and version control tools like GitHub
• Experience building reporting and dashboards in visualization tools like Hex, Claude-powered workflows, or similar platforms
• Strong data integrity mindset, with experience building reliable data pipelines, metric definitions, QA processes, and reporting standards
• Strong judgment on build vs. buy decisions, with the technical ability and willingness to build lightweight tools, workflows, and automations yourself when needed
• Experience in a scaled, high-performing analytics or data environment
• Full-stack mindset, with a willingness to solve problems end-to-end

Nice-to-Haves / Benefits

• Competitive salary and equity packages, including a 401k plan
• Remote-first culture
• 100% employer-covered comprehensive health, dental, and vision insurance
• Unlimited PTO policy
• Family-friendly environment; regular team events and offsites
• Unparalleled learning and professional development opportunities