• Design, develop, and maintain ETL processes and systems to support agency data integration needs. • Create and implement ETL strategies that meet LDWF and OTS requirements. • Collect, clean, and integrate data from various sources, including structured and unstructured data. • Develop and maintain data models and data mappings. • Ensure data quality and integrity by implementing data validation and error handling processes. • Collaborate with LDWF stakeholders and OTS technical teams to define and prioritize requirements. • Provide technical knowledge transfer, training, and documentation to OTS and LDWF agency staff for all requested work. • Participate in team meetings and design sessions by providing feedback and detailed design and implementation approaches in accordance with Scrum ceremonies. • Cooperate with LDWF's Technical Architect and other OTS technical teams to ensure compliance with OTS standards for state applications. • Perform additional tasks, special projects, analysis, studies, and plans as directed.

• Construir e manter modelos preditivos aplicados a decisões de negócio; • Estruturar, desenvolver e evoluir pipelines de dados robustos e escaláveis; • Apoiar as áreas de negócio com análises e garantir o funcionamento da cultura self-service de dados; • Otimizar, documentar e estruturar relatórios e dashboards no Looker; • Contribuir com as iniciativas de Inteligência Artificial em estágio de estruturação na empresa; • Suportar análises e projetos estratégicos de negócio com visão orientada a dados; • Compartilhar conhecimento e apoiar o desenvolvimento técnico do time.

Company: AHI agilon health, inc. Job Posting Location: Remote - USA Job Title: ​ Healthcare Analytics Engineer I Job Description: ​ Candidates must be legally authorized to work in the United States without employer sponsorship, now or in the future. At agilon health, you’ll join the Enterprise Analytics team dedicated to building data models, dashboards, and analytics tools that support business functions across the enterprise. As an Analytics Engineer I, you will contribute to the development and maintenance of reporting infrastructure while building foundational expertise in healthcare analytics and data engineering. You will work under the guidance of senior team members to support data modeling, pipeline monitoring, and analytics delivery efforts. This role is ideal for someone early in their analytics engineering career who is eager to learn, grow technical skills, and make an impact in transforming healthcare. To be considered, candidate must be located EST OR CST Essential Job Functions: - Support the design, development, and maintenance of data models for analytics and reporting - Assist in documenting standard tables, data sources, and basic relationships - Contribute to data quality initiatives by identifying inconsistencies and helping standardize definitions - Monitor existing data pipelines and escalate issues related to stability or timeliness - Partner with business and technical stakeholders to understand reporting requirements - Utilize SQL, Python, and related technologies to support data transformation and automation tasks Other Job Functions: - Understand, adhere to, and implement the Company’s policies and procedures - Demonstrate responsiveness and professionalism with internal stakeholders - Take initiative in developing technical and business knowledge - Communicate clearly and professionally, both verbally and in writing - Demonstrate reliability, accountability, and attention to detail in deliverables - Actively seek feedback and apply learnings to improve performance Required Qualifications: Minimum Experience - 1–3 years of experience working with data transformation, analytics, or ETL pipelines - Foundational proficiency in SQL - Working knowledge of Python or similar programming language Preferred Experience - Familiarity with cloud data platforms such as Snowflake or SQL Server - Exposure to dbt or modern data transformation frameworks - Foundational proficiency in VS code and Bitbucket - Interest in or exposure to healthcare data, particularly Medicare Advantage or value-based care models Education: - Bachelor’s Degree in mathematics, computer science, statistics, engineering, or related field required - Master’s degree preferred but not required Knowledge, Skills and Abilities: - Ability to understand business requirements and translate them into structured datasets with guidance - Strong analytical thinking and problem-solving skills - Clear written and verbal communication skills - Detail-oriented with strong organizational skills - Eagerness to learn new technologies and healthcare analytics concepts - Ability to document processes and maintain technical documentation Location: ​ Remote - PA Pay Range: ​ Salary range shown is a guideline. Individual compensation packages can vary based on factors unique to each candidate, such as skill set, experience, and qualifications.

• Bridge the gap between data engineering and analytics team • Transform raw data into scalable, trusted datasets • Deliver high-impact analytics solutions through modern BI visualization platform • Leverage cloud data platform • Design, build, and maintain scalable data models (dimensional, star/snowflake schemas) • Develop and optimize SQL / PL-SQL transformations for analytics consumption • Implement and manage semantic layers to standardize business logic and metrics • Ensure data quality, consistency, and governance across datasets • Develop and maintain dashboards, liveboards, and search-driven analytics (preferably in ThoughtSpot) • Translate business requirements into intuitive, self-service analytics solutions • Partner with stakeholders to define KPIs, metrics, and reporting standards • Work within Snowflake for data modeling, performance tuning, and cost optimization • Collaborate with data engineering teams on data pipelines and ingestion frameworks • Optimize query performance and warehouse utilization • Support embedded analytics use cases (APIs, SDKs, or iframe-based integrations) • Enable external and internal users with governed, scalable analytics access • Drive adoption of BI tools through best practices and training • Define and enforce standards for data modeling, naming conventions, and metric definitions • Contribute to data cataloging and documentation