Job Description :

As a Senior Data Engineer, you will design, build, and optimize the data pipelines and architectures that power Fluent Health. You will play a pivotal role in handling complex healthcare datasets, implementing event-driven streaming architectures, and enabling advanced analytics and AI capabilities. The ideal candidate is someone who thrives on solving complex data bottlenecks, champions data quality, and possesses a deep understanding of modern cloud data stacks.

Key Responsibilities :

- Data Infrastructure & Scaling : Architect, build, and maintain scalable, high-performance data pipelines (ETL/ELT) to process complex, large-scale healthcare datasets.

- Streaming & Event-Driven Architecture : Design and optimize real-time data ingestion pipelines utilizing Kafka and event-driven systems.

- Data Modeling & Analytics Engineering : Implement robust data modeling and analytics engineering best practices to transform raw data into clean, business-ready models.

- Governance & Compliance : Collaborate on building stringent data governance framework, ensuring high data quality, security, and compliance with healthcare standards.

- AI & Analytics Enablement : Partner with Data Science, Product, and AI teams to deliver reliable data foundations for predictive models and advanced healthcare analytics platforms.

- Mentorship & Best Practices : Promote engineering excellence by participating in code reviews, technical documentation, and mentoring junior/mid-level engineers.

Required Skills & Qualifications :

- Experience : 7- 9 years of dedicated experience in Data Engineering, with a proven track record of managing production-grade data infrastructure.

- Core Languages : Advanced, production-level expertise in Python and SQL.

- Cloud Data Warehousing : Hands-on experience architecting and managing solutions in at least one major cloud warehouse: Snowflake, BigQuery, Redshift, or ClickHouse.

- Orchestration & Transformation : Proficient with modern orchestration tools (Airflow, Dagster) and data transformation frameworks (dbt).

- Streaming & Messaging : Solid experience with Apache Kafka or similar event-driven architectures.

- Data Theory : Strong foundational knowledge in Data Modeling methodologies and Analytics Engineering concepts.

Preferred Qualifications :

- Experience working within the Healthcare or HealthTech domains (understanding of HIPAA, HL7, FHIR, or electronic health records is a major plus).

- Experience deploying data workflows within containerized environments (Docker, Kubernetes) and CI/CD pipelines.