Data Engineer – Healthcare Data & Analytics
Job Title: Data Engineer – Healthcare Data & Analytics
Experience: 5+ Years
Employment Type: Full-Time
Work Mode: Remote
Industry: Healthcare Technology
Job Summary
We are looking for an experienced Data Engineer to design, develop, and maintain scalable data platforms and analytics solutions for healthcare applications.
The ideal candidate will have strong hands-on experience with Snowflake, SQL, Python, Spark, Azure, Kubernetes, Airflow, and GitHub/CI/CD. Experience with Databricks and AI/ML model deployments is highly preferred.
The candidate will work closely with data engineers, data scientists, ML engineers, analysts, and business stakeholders to build reliable data pipelines, support analytics initiatives, and enable production deployment of AI/ML solutions in a healthcare environment.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and data processing solutions.
- Build and optimize data solutions using Snowflake, SQL, Python, and Spark.
- Develop data processing workflows using Apache Spark/PySpark.
- Work with Azure cloud services to build and support enterprise data solutions.
- Develop and manage data workflows and orchestration using Apache Airflow.
- Work with Databricks for data engineering and analytics workloads.
- Implement CI/CD pipelines using GitHub and related DevOps practices.
- Support deployment and operationalization of AI/ML models in production environments.
- Work with Kubernetes for containerized application and model deployments.
- Perform data validation, cleansing, transformation, and quality checks.
- Develop solutions that support healthcare data analytics and reporting requirements.
- Collaborate with Data Scientists, ML Engineers, Analysts, and business teams to deliver analytics-ready datasets.
- Troubleshoot data pipeline, application, and deployment issues.
- Optimize data processing jobs, SQL queries, and cloud resources for performance and scalability.
- Follow best practices for data security, governance, privacy, and compliance.
- Contribute to technical documentation, code reviews, testing, and Agile development activities.
Required SkillsData Engineering
- Strong experience with SQL
- Python
- Apache Spark / PySpark
- Snowflake
- Data Engineering and Data Pipeline Development
- Data Transformation and Data Quality
Cloud & Modern Data Platforms
- Microsoft Azure
- Databricks – Preferred
- Cloud-based data engineering and analytics
- Experience with scalable data processing architectures
DevOps & Deployment
- GitHub
- CI/CD pipelines
- Kubernetes
- Containerized application/model deployment
- Production deployment and troubleshooting
Data Orchestration
- Apache Airflow
- Workflow orchestration and scheduling
- Pipeline monitoring and troubleshooting
AI/ML
- Understanding of AI/ML model deployment
- Experience supporting ML model productionization
- Familiarity with ML pipelines and model serving is an advantage
Data Analytics
- Strong data analysis skills
- Data validation and profiling
- Data interpretation and troubleshooting
- Experience supporting business analytics and reporting
Healthcare Domain
Experience in the Healthcare domain is preferred.
Candidates with experience working with healthcare datasets, analytics platforms, clinical data, claims data, healthcare applications, or healthcare reporting solutions will be highly preferred.
Knowledge of healthcare data privacy, security, governance, and compliance requirements is an advantage.
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
- 5+ years of experience in Data Engineering, Data Analytics, or a related technical role.
- Strong hands-on experience with SQL, Python, Snowflake, and Spark.
- Experience working with Azure cloud environments.
- Experience with Airflow and CI/CD.
- Strong understanding of data engineering and analytics concepts.
- Excellent problem-solving and troubleshooting skills.
- Good communication and collaboration skills.
Preferred Qualifications
- Hands-on experience with Databricks.
- Experience with AI/ML model deployment and MLOps.
- Strong Kubernetes experience.
- Healthcare/Healthcare Technology domain experience.
- Experience with Azure data services.
- Knowledge of healthcare data standards and compliance.
- Experience working in Agile/Scrum environments.
Work Location: Hybrid remote in Remote
