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Analytics Engineer at Oscilar - ApplyBlast

Analytics Engineer

Oscilar

4 months ago

4.3 on Glassdoor

Remote

Full Time

Senior

3 applicants

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About this role

Analytics Engineer at Oscilar builds data foundations for scalable analytics across the organization, partnering with stakeholders to transform raw data into reliable metrics and insights.

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

Skills

Qualifications

5+ years of experience as an Analytics Engineer, Data Engineer, or in a similar Data Science & Analytics roleExperience partnering with GTM, Finance, and cross-functional leaders to build and report on company-wide metricsStrong SQL and Python skills, with the ability to transform raw data into clean, accurate, and scalable data modelsExperience building multi-step ETL workflows and robust data models using tools like dbtStrong 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

About Oscilar

oscilar.com

Headquarters

Palo Alto, California, United States

Company Size

51-200 employees

Founded

2021

View Profile

Oscilar is an AI-native, agentic risk platform built specifically for financial institutions, offering a coordinated suite of AI agents that handle detection, decisions, and resolution across fraud, credit, onboarding, and AML compliance. Its Agent Hub enables risk teams to build and deploy risk workflows in plain language, automate alert scoring and investigation narratives, and continuously refine recommendations through analyst feedback. The platform processes over 30 billion decisions per year, delivering real-time, explainable risk decisions with results such as 45% fewer false positives and 5x faster policy deployment.