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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Security Analytics Engineer L5 - **Company:** THENO DEVELOPMENT LLC - **Location:** Lehi, UT, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Artificial Intelligence, Data Analysis, Data Infrastructure, Apache Hive, Python (Programming Language), Raw Data, SQL Databases, Presto, Data Pipelines - **Published:** August 18, 2026 - **Apply:** https://www.workingnomads.com/job/go/1799489/ ## About the Role * Domain expertise in consumer product security, such as fraud, account security, abuse/trust & safety, authentication, or privacy, and fluency in how security risk gets measured and reported * Strong engineering fundamentals, including well written, tested, maintainable code, sound data modeling, and data pipelines built to scale * Expert in analytics (SQL, Presto, Spark SQL, Python), with strong critical thinking and a demonstrated ability to turn raw data into clear, compelling narratives * Quick to pick up new tools and techniques, including using AI/LLM-based tools to work faster and smarter across analysis, engineering, and reporting * Comfort operating in ambiguity, building a data model, portfolio, or dashboard from a 0-to-1 state and iterating with cross-functional input * A strong bias for action, comfortable moving fast, making decisions with incomplete information, and driving ideas to production rather than waiting for perfect conditions ## Description Our Analytics Engineers build the piece of that foundation that turns raw security data into a story people can act on: the pipelines, metrics, and dashboards that give every security team, and Netflix leadership, a clear, shared view of risk. What you will work on: As a Security Analytics Engineer on CSF, you will do the hands-on analytics that gets to the root of consumer risk, and build the data foundation, metrics, and dashboards that turn those findings into a single, trusted narrative that leadership, product partners, and other security teams can act on. * Drive the analytics behind device and authentication risk, digging into signals like device trust, login/auth protocols, and access patterns to surface where and how risk shows up for our members * Be a thought partner in shaping the strategy behind our consumer security risk metrics, deciding what the organization should measure and why, analyzing the underlying data to validate what's meaningful, and translating that into a dashboard that gives every security team a shared, current view of top risks * Define and evolve our consumer product risk portfolio, using data to quantify and prioritize the ground-truth inventory of risk areas across our security organization, driving alignment across teams and with the broader company risk registry * Influence how our organization's risk story is told at the leadership level, shaping the analysis and narrative behind quarterly risk reviews, monthly metrics reviews, and leadership-level cost-of-fraud reporting * Partner strategically with security PMs and product teams to define what a comprehensive security metrics and controls story looks like for each product vertical, and drive its adoption * Collaborate closely with threat-modeling partners to get ahead of emerging risks, using data to shape how they get measured and reported rather than reacting after the fact * Build and maintain the data pipelines and metrics that power our analytics and dashboards, and design solutions other consumer security teams can build on, driving down one-off tooling across the organization ## Related Videos - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Automated Security for the Entire SDLC](https://www.wearedevelopers.com/videos/100323-automated-security-for-the-entire-sdlc) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Bringing Clarity to Event Streams: Enabling Analytics and AI Through Rich Metadata](https://www.wearedevelopers.com/videos/1616-bringing-clarity-to-event-streams-enabling-analytics-and-ai-through-rich-metadata) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Why Your AI Agent Keeps Hallucinating Your Data: Building Deterministic Context Layers](https://www.wearedevelopers.com/videos/2055-why-your-ai-agent-keeps-hallucinating-your-data-building-deterministic-context-layers) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Trustworthy AI Starts at Deployment: 5 Checks Before You Ship](https://www.wearedevelopers.com/magazine/753-trustworthy-ai-starts-at-deployment-5-checks-before-you-ship) - [Dev Digest 134 - Where pixels sing?](https://www.wearedevelopers.com/magazine/477-dev-digest-134-where-pixels-sing) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)