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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Analytics Engineer - **Company:** The Information and Referral Federation of Los Angeles County - **Location:** United States (Remote available) - **Salary:** $105,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Data Analysis, Cloud Computing, Cloud Database, Code Review, Databases, Continuous Integration, Data Discovery, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Dimensional Modeling, Python (Programming Language), Key Management, Query Optimization, Systems Integration, Tableau (Software), Sql Optimization, Large Language Models, Analytic Functions, Git, Pandas, Containerization, Functional Programming, Cloudwatch, Restful APIs, Software Version Control, Data Pipelines - **Published:** July 31, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=395dca48176f846b ## About the Role * Advanced SQL, including aggregation, window/analytic functions, PARTITION expressions, row-level calculations, MERGE statements, and query tuning on columnar warehouses such as Redshift * Proficiency in Python for data engineering - pandas, connecting to databases, system-level file management, and writing testable, well-structured modules * Working knowledge of dbt (or an equivalent transformation framework): building version-controlled, modular models and a layered bronze/silver/gold architecture * Experience with RESTful APIs and integrating external data sources * Dimensional modeling and data-warehousing fundamentals * Building data-quality tests and schema-evolution workflows * Experience deploying and scheduling data jobs - batch pipelines, orchestration, and basic monitoring * Solid experience working in a cloud data environment, AWS preferred (S3, Redshift, Secrets Manager, CloudWatch, Lambda, Kinesis, Glue) * Ability to build and support BI reports in an industry-standard tool (Tableau preferred) * Practical experience applying AI/LLMs to real work, with a strong grasp of prompting fundamentals and advanced techniques (context management, structured output, evaluation) to produce reliable results * Version control (Git) and good coding practices - testing, code review, and documentation * A self-starter mindset: able to take on open-ended tasks and execute to a high standard with limited direction, * Experience productionizing pipelines: containerization, CI/CD, secrets management, observability/alerting, and operator runbooks * Familiarity with data discovery, crawling/scraping, and building LLM-in-the-loop evaluation workflows * Experience enabling analysts through self-service access, onboarding, and documentation * Experience with extract-layer tooling like Fivetran or Stitch * Advanced BI tool experience, including administration of a Tableau Cloud environment, dashboarding, and geospatial visualization Disaster Response Expectations: 211 LA serves as a critical component of Los Angeles County's emergency response network. While this is a primarily remote position with standard business hours, employees are required to support emergency operations outside of normal working hours during declared disasters, public emergencies, or other critical incidents. The Analytics Engineer should be able to respond to urgent requests with flexibility and professionalism, helping ensure that accurate, timely data and reporting are available to support operational decision-making. Such situations are infrequent but are an essential part of supporting 211 LA's mission and the communities we serve., * Ability to lift up to 20 pounds. * Prolonged periods sitting at a desk and working on a computer. ## Description The Analytics Engineer is a new role on the 211LA DAIS team, created to help develop and own the next-generation data pipeline that anchors our 2026/7 roadmap. The ideal hire is a self-starter who can take open-ended problems and produce high-quality solutions. They're a strong practitioner of applied AI who understands both foundational and advanced techniques for coaxing excellent output from large language models. They bring a solid command of the modern analytics engineering stack to bear for building and maintaining our full analytics pipeline., * Develop, own, and maintain the Data team ETL pipeline * Build and maintain version-controlled dbt models and a consistent bronze/silver/gold layer shared across the team * Support dataset discovery and qualification using deep-search techniques. Onboard discovered data sources from extraction to analytics data mart. * Deploy, schedule, and monitor data jobs; diagnose and resolve pipeline failures * Apply AI/LLMs thoughtfully across the pipeline to keep pace with an ambitious roadmap while keeping output reliable * Build and support BI reports for program managers and mid-to-senior leadership * Take open-ended initiatives from scoping through production delivery with high quality * Organize and maintain code, tests, and documentation using version control ## Related Videos - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [WeAreDevelopers LIVE - CSS is DOOMed](https://www.wearedevelopers.com/videos/1838-wearedevelopers-live-css-is-doomed) - [Getting to Know Your Legacy (System) with AI-Driven Software Archeology](https://www.wearedevelopers.com/videos/1437-getting-to-know-your-legacy-system-with-ai-driven-software-archeology) - [Applying Agile Principles to Incident Management ](https://www.wearedevelopers.com/videos/101-applying-agile-principles-to-incident-management) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Prompt Engineering is a Job of the Past](https://www.wearedevelopers.com/magazine/342-prompt-engineering-is-a-job-of-the-past) - [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)