Sr. Data Platform Engineer - GenAI Apps

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Requirements:

• Excellence in quality data pipeline design, development, and optimization to create reliable, modular, secure data foundations for the organization's data delivery system from applications to analytics & ML
• Expertise in Python, SQL, and familiarity with AWS tools, Databricks, and DBT.
• Strong understanding of database structure systems and data mining.
• Innate aptitude for interpreting complex datasets with demonstrated ability to discern underlying patterns, identify anomalies, and extract meaningful insights, demonstrating advanced data intuition and analytical skills.
• Proven ability to independently handle ambiguous project requirements and lead data initiatives from start to finish, while collaborating extensively with cross-functional, non-technical teams to inform and shape product development.

Responsibilities:

• Lead the design, development, and management across investments to platform, model infrastructure, and data pipelines in support of data intensive AI solutions.
• Work closely with a close knit team of solution experts & innovators to design, iterate, and develop key pipelines to unlock new solution functionality, analytical insights, and machine learning features.
• Identify, monitor, and lead initiatives to ensure our data platform remains scalable, reliable, and efficient in light of evolving data requirements of our products and services - particularly in the rapidly changing Gen AI / LLM ecosystem
• Partner with cross-functional stakeholders & peers to translate data needs into technical solutions with rigorous technical scope to enable more junior engineers
• Spearhead the discovery, evaluation, and integration of new datasets, collaborating (incl. pipeline development and data modeling/documentation), working closely with key data stakeholders to understand their impact and relevance to our core products and the healthcare domain.
• Translate product / analytical vision into highly functional data pipelines supporting high quality & highly trusted data products (incl. designing data structures,  building and scheduling data transformation pipelines,  improving transparency etc.).
• Engage in the rapid new AI product development from concept to deployment, ensuring robust platform supporting easy iteration and monitoring.
• Set the standard for data engineering practices within the company, guiding the architectural approaches, data pipeline designs, and the integration of cutting-edge technologies to foster a culture of innovation and continuous improvement.