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
Proficiency in data analysis tools (eg. SQL) and experience with data visualization tools
Excellent problem-solving skills and the ability to work with large, complex datasets
Solid understanding of data governance frameworks, tools, and best practices.
Knowledge of data protection regulations and compliance requirements
Good-to-Have Skills
Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development
Good understanding of data modeling, data warehousing, and data integration concepts
Knowledge of Python/R, Databricks, SageMaker, cloud data platforms
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.
Professional Certifications
Certified Data Engineer / Data Analyst (preferred on Databricks or cloud environments)
Soft Skills
Excellent critical-thinking and problem-solving skills
Good communication and collaboration skills
Demonstrated awareness of how to function in a team setting
Demonstrated presentation skills
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