Data Engineer II

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About mPulse: mPulse is the leader in conversational AI and member engagement for healthcare. We partner with the nation's most innovative health plans — Medicare Advantage, Medicaid, and Commercial — to engage members in conversations that close care gaps, improve Stars ratings, and drive better health outcomes. Our platform reaches tens of millions of Americans and is built on the belief that better health starts with better conversations. Job Summary: mPulse is seeking a highly motivated and detail-oriented Data Engineer II to join our Data Engineering team. In this role, you will design, develop, and maintain scalable data pipelines and platform capabilities that support our analytics, product, and AI/ML initiatives. Our data platform processes high-volume, high-velocity healthcare data, enabling insights and data-driven solutions for a growing client base. You will work cross-functionally with Data Operations, Product, Analytics, and Data Science teams to ensure data is reliable, performant, and aligned with business needs. The ideal candidate brings strong experience in SQL, Python, dbt, and Airflow, along with a solid foundation in data warehousing and a passion for solving complex data challenges in a healthcare environment. Duties/Responsibilities: Design, develop, and maintain scalable data pipelines (ETL/ELT) to support ingestion, transformation, and delivery of high-volume healthcare data. Write, optimize, and maintain complex SQL queries for data transformation, validation, and performance tuning. Develop and manage workflow orchestration using Apache Airflow, including DAG creation, monitoring, and troubleshooting. Enhance and scale data platform capabilities to support analytics, product features, and AI/ML use cases. Build and maintain data quality frameworks, including automated data profiling, validation, and testing processes. Monitor and optimize pipeline performance, reliability, and efficiency in production environments. Analyze complex data issues, identify root causes, and implement scalable solutions, clearly communicating findings to both technical and non-technical stakeholders. Collaborate with cross-functional teams (Data Operations, Product, Analytics, Data Science) to gather requirements and deliver high-quality data solutions. Partner with clinical and analytics teams to operationalize data-driven insights and reporting solutions. Contribute to documentation of data pipelines, data models, and engineering processes to support maintainability and knowledge sharing. Skills/Abilities/Experience: Strong proficiency in SQL, including complex querying, data transformation, and performance optimization. Proficiency in Python for data processing, automation, and integration tasks. Experience designing and building data pipelines (ETL/ELT) to support data ingestion, transformation, and delivery. Hands-on experience with modern data warehousing platforms, such as Snowflake, PostgreSQL, Amazon Redshift, or Microsoft SQL Server. Experience with workflow orchestration tools, particularly Apache Airflow (DAG development, debugging, and maintenance). Experience using dbt (data build tool) to develop, test, and manage modular data transformation workflows. Experience working with cloud platforms, particularly AWS (e.g., S3, RDS, Lambda, Glue, DMS). Experience with version control systems and collaborative development workflows, such as GitHub or Bitbucket. Familiarity with CI/CD practices and tools, such as Jenkins or GitHub Actions. Experience supporting data quality initiatives, including data profiling, validation, or monitoring frameworks. Familiarity with data modeling and data warehousing concepts, including dimensional modeling. Exposure to analytics, reporting, or data visualization tools (e.g., Tableau, Looker) is a plus. Experience working with healthcare data, including claims or clinical datasets, is a plus. Familiarity with data science or machine learning workflows from a data engineering perspect

关于mPulse：mPulse是医疗保健领域对话式AI和会员互动方面的领导者。我们与美国最具创新性的健康计划——Medicare Advantage、Medicaid和Commercial——合作，让会员参与对话，从而弥合护理差距、提升Stars评级并推动更好的健康结果。我们的平台覆盖数千万美国人，并建立在“更好的健康始于更好的对话”这一信念之上。职位摘要：mPulse正在寻找一位高度积极且注重细节的Data Engineer II加入我们的Data Engineering团队。在这一角色中，您将设计、开发和维护可扩展的数据管道和平台能力，以支持我们的分析、产品和AI/ML计划。我们的数据平台处理高容量、高速度的医疗保健数据，为不断增长的客户群提供洞察和数据驱动解决方案。您将与Data Operations、Product、Analytics和Data Science团队跨职能合作，确保数据可靠、高性能并符合业务需求。理想的候选人应在SQL、Python、dbt和Airflow方面具有丰富经验，并具备扎实的数据仓库基础，以及热衷于在医疗保健环境中解决复杂数据挑战。职责/责任：设计、开发和维护可扩展的数据管道（ETL/ELT），以支持高容量医疗保健数据的摄取、转换和交付。编写、优化和维护复杂的SQL查询，用于数据转换、验证和性能调优。使用Apache Airflow开发和管理工作流编排，包括DAG创建、监控和故障排除。增强并扩展数据平台能力，以支持分析、产品功能和AI/ML用例。构建和维护数据质量框架，包括自动化数据剖析、验证和测试流程。在生产环境中监控并优化管道性能、可靠性和效率。分析复杂数据问题，识别根本原因，并实施可扩展的解决方案，清晰地向技术和非技术利益相关者传达发现。与跨职能团队（Data Operations、Product、Analytics、Data Science）合作，收集需求并交付高质量的数据解决方案。与临床和分析团队合作，将数据驱动的洞察和报告解决方案投入运营。参与数据管道、数据模型和工程流程的文档编写，以支持可维护性和知识共享。技能/能力/经验：精通SQL，包括复杂查询、数据转换和性能优化。熟练使用Python进行数据处理、自动化和集成任务。具有设计和构建数据管道（ETL/ELT）以支持数据摄取、转换和交付的经验。具有现代数据仓库平台的实践经验，如Snowflake、PostgreSQL、Amazon Redshift或Microsoft SQL Server。具有工作流编排工具的经验，尤其是Apache Airflow（DAG开发、调试和维护）。具有使用dbt（data build tool）开发、测试和管理模块化数据转换工作流的经验。具有云平台经验，尤其是AWS（例如S3、RDS、Lambda、Glue、DMS）。具有版本控制系统和协作开发工作流的经验，如GitHub或Bitbucket。熟悉CI/CD实践和工具，如Jenkins或GitHub Actions。具有支持数据质量计划的经验，包括数据剖析、验证或监控框架。熟悉数据建模和数据仓库概念，包括维度建模。接触过分析、报告或数据可视化工具（例如Tableau、Looker）者优先。具有医疗保健数据经验，包括索赔或临床数据集者优先。从数据工程角度熟悉数据科学或机器学习工作流。

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