Senior Data Engineer

• Design, develop, and optimize data services and solutions required to support various company products (like FeatureStore or synthetic data management)
• Work closely with data analysts, data scientists, engineers, and cross-functional teams to understand data requirements and deliver high-quality solutions.
• Design and integrate LLM- and agent-based capabilities into data platforms and services, enabling smarter data operations and AI-driven data products.
• Design, develop, and optimize scalable data pipelines to ensure data is clean, accurate, and ready for analysis.
• Build and maintain robust data models that support clinical, business intelligence, and operational needs.
• Implement and enforce data quality standards, monitoring, and best practices across systems and pipelines.
• Manage and optimize large-scale data storage and processing systems to ensure reliability and performance.

• 5+ years of experience as a Data Engineer / Backend Engineer (with strong emphasis on data processing)
• Python Proficiency: Proven ability to build services, solutions, data pipelines, automations, and integration tools using Python.
• SQL Expertise: Deep experience in crafting complex queries, optimizing performance, and working with large datasets.
• Strong knowledge of data modeling principles and best practices for relational and dimensional data structures.
• A passion for maintaining data quality and ensuring trust in business-critical data.

• Experience with cloud platforms (e.g., AWS, GCP, or Azure) for data engineering and storage solutions.
• Knowledge of data orchestration tools (e.g., Airflow)
• Understanding of CI/CD practices and version control systems.
• Experience with Kubernetes.
• Experience in ML/AI development.

Competitive compensation packages based on industry benchmarks for function, level, and geographic location.