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

Bachelor's or Master's 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