• Identify and incorporate data sources to enhance cyber analytics tools • Integrate and automate services and operational tasks by consuming and building APIs, tools, and frameworks • Work with security telemetry tools, SIEM solutions, and other data metric reporting products • Synthesize disparate data points to create comprehensive security insights • Establish predictive narratives to preemptively identify potential attacks • Enhance decision-making processes through clear and actionable information • Progress maturity of security analytics capabilities • Provide metrics and reporting capabilities for quantitative security dashboards • Ensure Global Security Strategy meets security and privacy needs • Develop Security Orchestration and Automation Response (SOAR) capabilities • Facilitate the information security risk assessment process

Role 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. Key Responsibilities - 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 Qualifications - 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 Preferred Qualifications - 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. Compensation $105,000 annually, commensurate with experience. Benefits - Comprehensive health and wellness benefits - Retirement savings plan - Professional development opportunities - Flexible work arrangements - Employee assistance program Physical Demands & Working Conditions - Ability to lift up to 20 pounds. - Prolonged periods sitting at a desk and working on a computer. Equal Opportunity Employer 211LA is an Equal Opportunity Employer and values diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.

Role Description - Develop and implement strategies to improve supply chain efficiency. - Monitor and analyze supply chain performance metrics to identify areas for improvement. - Collaborate with cross-functional teams to coordinate logistics, procurement, and inventory management activities. - Lead supplier relationship management initiatives to drive cost savings and ensure quality standards are met. - Manage inventory levels and optimize supply chain inventory processes. - Oversee logistics operations and transportation planning to optimize delivery schedules. - Stay informed about industry trends and best practices to continuously improve supply chain operations. Qualifications - Bachelors - Business Analytics - Bachelors - Computer Science - Bachelors - Statistics - Masters - Data Science Requirements - APICS Certified in Production and Inventory Management (CPIM) - Lincoln Land - APICS - Certified Supply Chain Professional certification (CSCP) - American Production and Inventory Control Society (APICS) - Certified Professional in Supply Management (CPSM) - Institute for Supply Management (ISM) - Certified Supply Chain Professional (CSCP) - Indian Institute of Management, Trichy Benefits - Lead AI-powered transformation – Drive innovation and solve real-world business challenges that matter. - Make an impact – Help global enterprises solve business challenges that matter. - Accelerate your career – Gain hands-on experience, mentorship, and world-class learning opportunities to stay ahead. - Work with the best – Join 140,000+ bold thinkers and problem-solvers who push boundaries every day. - Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress.

Role Description Our client is expanding its modern data and analytics capabilities and is seeking a Senior Analytics Engineer with strong expertise in analytics engineering, dimensional data modeling, DBT, and cloud-based data platforms. This role is heavily focused on designing and building scalable analytical data models that support reporting, business intelligence, and modern analytics initiatives across internal departments. The ideal candidate is a strong SQL and analytics engineering professional who can work independently, communicate effectively with stakeholders, and deliver production-ready data solutions in enterprise environments. Key Responsibilities - Analytics Engineering & Data Modeling (Primary Focus) - Design and implement scalable analytical data models using dimensional modeling best practices - Build and maintain fact tables, dimension tables, star schemas, and reporting datasets - Develop and manage DBT transformations, models, and analytics workflows - Create scalable ELT pipelines using Databricks, SQL, Python, and cloud-based technologies - Collaborate with stakeholders to translate business and reporting requirements into reliable data solutions - Ensure data quality, consistency, and governance across analytics environments - Support modern analytics initiatives using Microsoft Fabric, SQL endpoints, and related tooling - Use Terraform or Infrastructure as Code (IaC) tooling to manage data platform resources - Contribute to AI-enabled analytics initiatives, integrations, and modern data platform enhancements. - Secondary Responsibilities - Provide light support for legacy Microsoft reporting environments (SSRS), on an as-needed basis only. Qualifications - Strong hands-on experience with DBT and analytics engineering workflows, including deep expertise in dimensional data modeling: - Facts and dimensions - Star schema design - Kimball methodology - Analytical warehouse modeling - Hands-on experience with Databricks, including SQL, Python, and PySpark; advanced SQL skills for data transformation and analytics engineering - Experience using Terraform or Infrastructure as Code (IaC) tooling - Experience with Microsoft Fabric, especially SQL endpoints and analytics workloads - Experience supporting AI-enabled analytics initiatives, copilots, agents, or modern AI integrations - Strong communication and stakeholder-management skills - Ability to work independently in a fast-paced remote environment Nice-to-Have Skills - Familiarity with Power BI or enterprise reporting environments - Experience modernizing legacy BI/data environments - Familiarity with Azure Data Factory, Synapse, or related Microsoft cloud analytics services - Experience with data quality frameworks, monitoring, or testing practices Who You Are - You are an analytics-focused data professional with strong business and technical understanding - You excel at translating reporting and analytics requirements into scalable data models - You are comfortable working independently and collaborating across multiple teams - You bring strong ownership, communication, and problem-solving skills - You are confident explaining technical concepts to both technical and non-technical stakeholders Non-Technical Requirements - Strong spoken English - Reliable home/office connectivity and consistent meeting/standup attendance - Full Mountain Time working-hours overlap required Engagement Details - Independent contractor role - Fully remote - 32 - 40 hours per week - Full-time, long-term commitment - Hourly rate: $23.75–$25 USD depending on experience