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# Scaled Insights Analyst, Intelligence and Scaled Insights, YouTube

- **Company:** LOON LLC
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $141,000.0 - $205,000.0
- **Contract:** Permanent contract
- **Skills:** Big Data, Data Architecture, Data Integration, Extract Transform Load (ETL), Data Systems, Data Warehousing, Apache Hadoop, Python (Programming Language), SQL Databases, Unstructured Data, Freeform SQL, Large Language Models, Apache Spark, Information Technology, Data Management, Data Pipelines
- **Published:** September 22, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=2ea63f521379a40a

## About the Role

* Bachelor's degree in Computer Science, Engineering, a related technical field, or equivalent practical experience.
 * 7 years of experience coding in Python and SQL.
 * 7 years of experience designing, deploying, and managing data pipelines, including schema management, data modeling, exploratory querying, and data workflows., * Experience with data warehousing or data modeling concepts.
 * Experience with big data technologies (e.g., Hadoop, Spark, Python, or R).
 * Experience with translating business requirements to BI solutions.
 * Experience with explaining technical analysis to stakeholders.

## Description

* Design, build, and optimize robust, production-grade data architecture and ETL pipelines. Serve as the technical steward for the team's data platforms, ensuring maximum data reliability, integrity, and scalable governance across complex datasets.
 * Partner closely with stakeholders to translate ambiguous product and threat-intelligence analytical needs into structured data models, pipelines, and self-serve services.
 * Design, implement, and evaluate intelligent, agentic analytics systems leveraging Large Language Models (LLMs) to automate deep insight generation, anomaly detection, and operational workflows.
 * Architect and maintain internal tools, frameworks, and foundational tables that enable self-serve analytics, reducing data friction and dependencies for non-technical stakeholders. Streamline complex SQL queries and scale value-creating data integrations into automated, repeatable workflows.
 * Own ambiguous, non-routine technical challenges end-to-end. Identify latent infrastructure vulnerabilities, process messy unstructured data volumes, and apply advanced data modeling frameworks with minimal supervision.