Sr. Data Engineer

Responsibilities Gather and process large datasets from various internal and external sources, ensuring data accuracy and integrity. Develop and maintain data pipelines and ETL processes for both Snowflake and Palantir environments. Conduct exploratory data analysis, hypothesis testing, and root cause analysis on data sources and datasets. Synthesize complex data into actionable insights for stakeholders, including engineers, architects, data scientists, business and technical leaders. Collaborate with data scientists and engineering teams to support the development of rules-based algorithms, predictive models, and AI/ML or Generative AI solutions. Provide data inputs, feature engineering, and performance analysis to enhance model accuracy and reliability. Design and create dashboards, data visualizations, and presentations to communicate insights effectively to non-technical stakeholders. Document and present complex methodologies and outcomes in a clear, concise manner for both technical and non-technical audiences. Ensure that data management practices align with privacy and compliance standards relevant to public health. Establish and maintain data governance frameworks, data dictionaries, and standard operating procedures.Required Skills Strong SQL skills and experience working with cloud data warehousing platforms such as Snowflake. (5+ years) Proficiency in programming languages (Python, R, or similar) for data analysis and basic scripting. (3+ years) Proven track record in translating business questions into analytical problems and delivering actionable insights. (8+ years) Familiarity with ML concepts (feature engineering, model evaluation) and AI/ML frameworks (TensorFlow, PyTorch, scikit-learn, etc.). Excellent verbal and written communication skills, particularly in conveying technical information to diverse audiences. Ability to collaborate in cross-functional teams (data science, IT, clinical teams, etc.) to deliver end-to-end solutions.Preferred Skills Demonstrated ability to use Palantir Foundry (or similar Palantir platforms) for data integration, analysis, and collaboration. Hands-on experience with Generative AI models (e.g., GPT, BERT), and a strong understanding of large language models. Practical exposure to building end-to-end predictive and prescriptive analytics solutions in a healthcare or public health context. Experience leading or managing data analytics projects through the entire lifecycle, from requirements gathering to deployment and maintenance. Familiarity with agile methodologies and cross-functional team leadership. Proficiency in BI/reporting tools such as Tableau, Power BI, or Qlik to develop interactive dashboards and reports. Proven ability to provide insights from complex datasets using advanced visualization techniques.