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