Data Engineer

Career Category Engineering Job Description Level 4 Data Engineer:  What you will do  Let’s do this. Let’s change the world. In this vital role you will be responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions. This role involves working with large datasets, developing reports, supporting and performing data governance initiatives and, visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has deep technical skills, experience with database technologies, and a deep understanding of data architecture and ETL processes.  Roles & Responsibilities:  Design, develop, and maintain data solutions for data generation, collection, and processing  Be a crucial team member that assists in design and development of the data pipeline  Build data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems  Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions  Hands-on experience designing, developing, and implementing AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector search, tokenization, prompt engineering, and AI-assisted development tools such as OpenAI Codex, GitHub Copilot, or equivalent platform.  Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks  Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs  Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency  Implement data security and privacy measures to protect sensitive data  Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions  Collaborate and communicate effectively with product teams  Collaborate with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines to meet fast-paced business needs across geographic regions  Identify and resolve complex data-related challenges  Adhere to best practices for coding, testing, and designing reusable code/component  Explore new tools and technologies that will help to improve ETL platform performance  Participate in sprint planning meetings and provide estimations on technical implementation  What we expect of you  We are all different, yet we all use our unique contributions to serve patients.  Basic Qualifications:  Master’s/ Bachelor's degree and 5 - 9 years of Computer Science, IT or related field experience  Preferred Qualifications:  Must-Have Skills:  Hands-on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing