Job Title
Senior Data Engineer
Experience
5+ Years
Employment Type
Full-Time
Work Mode
Remote
Job Summary
We are seeking an experienced Senior Data Engineer to design, develop, and maintain scalable enterprise data platforms and cloud-native data solutions. The ideal candidate will have strong expertise in Snowflake, Python, Azure, Spark, SQL, Airflow, and Kubernetes, with experience building high-performance data pipelines, supporting AI/ML model deployments, and enabling advanced analytics.
The successful candidate will collaborate with data scientists, analysts, and engineering teams to deliver reliable, secure, and scalable data solutions while ensuring high data quality and operational excellence. Experience in the Healthcare domain is highly preferred.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT pipelines and enterprise data workflows.
- Build and optimize data pipelines using Snowflake, Python, SQL, Spark, and Azure.
- Develop and manage workflow orchestration using Apache Airflow.
- Design and implement cloud-based data solutions on Microsoft Azure.
- Support deployment and operationalization of AI/ML models in production environments.
- Optimize data processing performance, scalability, and reliability.
- Manage and process structured and unstructured data from multiple sources.
- Implement CI/CD best practices using GitHub.
- Work with Kubernetes to deploy and manage containerized data applications.
- Ensure data quality, governance, security, and compliance across enterprise platforms.
- Troubleshoot production issues and provide ongoing support for data pipelines.
- Collaborate with business stakeholders, data scientists, and cross-functional teams to deliver high-quality data solutions.
Required SkillsData Engineering
- Snowflake
- Python
- SQL
- Apache Spark
- ETL/ELT Development
- Data Pipeline Development
- Data Modeling
- Data Warehousing
- Data Analytics
Cloud & DevOps
- Microsoft Azure
- Kubernetes
- GitHub (CI/CD)
- Apache Airflow
AI/ML
- AI/ML Model Deployment
- MLOps fundamentals
- Production Model Support
Data & Analytics
- Data Transformation
- Data Integration
- Performance Optimization
- Data Quality & Validation
- Troubleshooting & Production Support
Preferred Skills
- Databricks
- Healthcare domain experience
- Experience with modern cloud data architectures
- Knowledge of DevOps best practices
- Exposure to Infrastructure as Code (IaC)
Required Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
- 5+ years of hands-on experience in Data Engineering.
- Strong experience with Snowflake, Python, Azure, Spark, SQL, Airflow, Kubernetes, and GitHub CI/CD.
- Experience deploying and supporting AI/ML models in production.
- Strong understanding of cloud-based data engineering and analytics platforms.
- Excellent analytical, problem-solving, and communication skills.
- Ability to work effectively in a remote, collaborative environment.
Preferred Qualifications
- Experience in the Healthcare domain.
- Experience with Databricks.
- Azure or Snowflake certifications.
- Experience working in Agile/Scrum environments.
Success Measures
- Successful delivery of scalable and reliable data engineering solutions.
- High availability and performance of enterprise data pipelines.
- Efficient deployment and monitoring of AI/ML models.
- Improved data quality, governance, and operational efficiency.
- Strong collaboration with cross-functional engineering and analytics teams.
- Timely resolution of production issues and continuous platform enhancements.
Work Location: Hybrid remote in Remote
