Lead Data Engineer

Job Summary:

The Data Engineer designs builds and maintains scalable data pipelines and infrastructure to support AI-driven healthcare SaaS applications. This role ensures data integrity security and compliance while enabling advanced analytics and machine learning capabilities. The Data Engineer collaborates with cross-functional teams to deliver reliable data solutions that improve clinical and operational outcomes.

Key Responsibilities:

1. Data Pipeline Development & ETL/ELT

• Expertise in building robust ETL/ELT pipelines using tools like Apache Airflow Talend or Informatica
• Ability to transform raw healthcare data into structured formats for analytics and AI models

1. Cloud Platform & Big Data Technologies

• Proficiency in AWS Azure or GCP for cloud-native development
• Experience with big data frameworks such as Spark Hadoop Hive

1. Healthcare Data Standards & Compliance

• Familiarity with HIPAA HL7 and FHIR standards
• Ability to ensure secure and compliant data handling across systems

1. AI & Machine Learning Integration

• Support for AI/ML model deployment and data preparation
• Understanding of model monitoring feature engineering and real-time data streaming

1. Technical Leadership

• Lead team to deliver planned commitments on time
• Learn understand and leverage cutting edge technologies to gain competitive advantage
• Creatively brainstorm and innovate on prototypes as well as future products and features to drive the business forward
• Proactively research industry trends and best practices to apply them as necessary
• Deliver high-quality and on-schedule work according to Agile software development methodology
• Participate in Agile activities including daily stand ups estimations and backlog grooming and reviews

• Provide internal development support which includes delivering fast and high-quality fixes to urgent production issues

1. Database Management & Optimization

• Strong SQL skills for complex queries joins and performance tuning
• Experience with relational and NoSQL databases (e.g. PostgreSQL MongoDB)

Required Qualifications:

Education & Experience

Bachelors or Masters degree in Computer Science Data Science or related field

10-14 years of experience in data engineering preferably in healthcare or SaaS
Experience with cloud platforms data pipeline tools and healthcare data standards
Exposure to AI/ML workflows and real-time analytics is a plus

Other Preferred Knowledge Skills Abilities or Certifications:

• Cloud Certifications: AWS Data Analytics Azure Data Engineer Google Cloud Data Engineer
• Streaming & Real-Time Data: Apache Kafka Spark Streaming Flink
• DataOps & Automation: Airflow dbt CI/CD for data workflows
• Security & Compliance: HIPAA GDPR CCPA data encryption
• Advanced Databases: PostgreSQL MongoDB Cassandra DynamoDB
• AI/ML Support: Feature engineering model monitoring ML pipeline integration