oscilar - Analytics Engineer
Requirements
• We are looking for someone who knows what best-in-class data and analytics infrastructure looks like, ideally from experience in a scaled, high-performing company, but who is also excited to build in a fast-moving startup environment. You should be nimble, hands-on, and opinionated about when to build versus buy, with the ability to build lightweight internal tools, workflows, and analytics products yourself when that is the fastest or highest-leverage path. • 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, with a clear understanding of what best-in-class looks like. • Full-stack mindset, with a willingness to solve problems end-to-end even when they fall outside a narrow job description.
Responsibilities
• Understand stakeholder data needs across Ops, Finance, and the GTM org, including Sales, Marketing, BDR, and Customer Success, and translate those needs into clear 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 to ensure 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 across the company. • Bring a strong point of view on build vs. buy decisions across the GTM data stack, identifying where Oscilar should use off-the-shelf tools versus where we should build internally for speed, leverage, or differentiation. • 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 as Oscilar scales.
Benefits
• Compensation: Competitive salary and equity packages, including a 401k plan. • Flexibility: Remote-first culture. • Health: 100% employer-covered comprehensive health, dental, and vision insurance with a top-tier plan for you and your dependents. (US) • Balance: Unlimited PTO policy. • Culture: Family-friendly environment; regular team events and offsites. • Development: Unparalleled learning and professional development opportunities. • Impact: Making the internet safer by protecting online transactions.
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