Designs and implements scalable Databricks Lakehouse solutions, including batch and real-time pipelines, data integration, governance, security, and quality frameworks. Leads technical architecture for analytics workloads, optimizes performance and costs, supports cloud migration and warehouse modernization, documents standards, and resolves complex platform issues. Collaborates with stakeholders and technical teams to deliver healthcare data platforms supporting reporting and operational decisions.
Databricks Data engineer (Remote, USA)
Position Summary
We are seeking an experienced Databricks Solution Architect to join our growing healthcare analytics team. This is a full-time, remote position based in the United States. The ideal candidate will have strong hands-on experience designing and implementing scalable data solutions on Databricks and cloud platforms, with a deep understanding of healthcare data and modern data architecture.
This role is an individual contributor position responsible for solution design, technical leadership, and delivering high-quality data platforms that support analytics, reporting, and operational decision-making.
Key Responsibilities
- Design and implement scalable data solutions using Databricks Lakehouse architecture.
- Develop and optimize batch and real-time data pipelines for large-scale data processing.
- Lead technical solution design for data integration, transformation, and analytics workloads.
- Collaborate with business stakeholders, data engineers, analysts, and product teams to translate requirements into technical solutions.
- Implement data governance, security, and data quality best practices using Unity Catalog and related technologies.
- Optimize performance, reliability, and cost efficiency of Databricks workloads.
- Support data warehouse modernization and cloud migration initiatives.
- Create architecture documentation, technical standards, and design guidelines.
- Troubleshoot complex data platform issues and provide technical recommendations.
- Stay current with Databricks and cloud platform capabilities and drive adoption of best practices.
Required Qualifications
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
- Minimum 5 years of experience in data engineering, data architecture, or related technical roles.
- Hands-on experience with Databricks in enterprise environments.
- Strong knowledge of PySpark, Spark SQL, Python, and SQL.
- Experience designing and implementing Lakehouse architectures.
- Experience building scalable ETL/ELT data pipelines.
- Strong understanding of data modeling, data warehousing, and analytics platforms.
- Experience working with structured and unstructured data.
- Strong problem-solving and communication skills.
- Ability to work independently in a remote environment.
- Experience implementing data governance and security frameworks.
Preferred Qualifications
- Experience in the healthcare industry, including claims, clinical, provider, member, or revenue cycle data.
- Experience with Azure, AWS, or GCP cloud platforms.
- Exposure to machine learning and AI/ML workloads on Databricks.
Certifications
Required:
- Databricks Certified Data Engineer Associate
- Databricks Certified Data Engineer Professional
Preferred:
- Cloud platform certifications (Azure, AWS, or GCP)
Responsibilities
Databricks Data engineer (Remote, USA)
Position Summary
We are seeking an experienced Databricks Solution Architect to join our growing healthcare analytics team. This is a full-time, remote position based in the United States. The ideal candidate will have strong hands-on experience designing and implementing scalable data solutions on Databricks and cloud platforms, with a deep understanding of healthcare data and modern data architecture.
This role is an individual contributor position responsible for solution design, technical leadership, and delivering high-quality data platforms that support analytics, reporting, and operational decision-making.
Key Responsibilities
- Design and implement scalable data solutions using Databricks Lakehouse architecture.
- Develop and optimize batch and real-time data pipelines for large-scale data processing.
- Lead technical solution design for data integration, transformation, and analytics workloads.
- Collaborate with business stakeholders, data engineers, analysts, and product teams to translate requirements into technical solutions.
- Implement data governance, security, and data quality best practices using Unity Catalog and related technologies.
- Optimize performance, reliability, and cost efficiency of Databricks workloads.
- Support data warehouse modernization and cloud migration initiatives.
- Create architecture documentation, technical standards, and design guidelines.
- Troubleshoot complex data platform issues and provide technical recommendations.
- Stay current with Databricks and cloud platform capabilities and drive adoption of best practices.
Required Qualifications
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
- Minimum 5 years of experience in data engineering, data architecture, or related technical roles.
- Hands-on experience with Databricks in enterprise environments.
- Strong knowledge of PySpark, Spark SQL, Python, and SQL.
- Experience designing and implementing Lakehouse architectures.
- Experience building scalable ETL/ELT data pipelines.
- Strong understanding of data modeling, data warehousing, and analytics platforms.
- Experience working with structured and unstructured data.
- Strong problem-solving and communication skills.
- Ability to work independently in a remote environment.
- Experience implementing data governance and security frameworks.
Preferred Qualifications
- Experience in the healthcare industry, including claims, clinical, provider, member, or revenue cycle data.
- Experience with Azure, AWS, or GCP cloud platforms.
- Exposure to machine learning and AI/ML workloads on Databricks.
Certifications
Required:
- Databricks Certified Data Engineer Associate
- Databricks Certified Data Engineer Professional
Preferred:
- Cloud platform certifications (Azure, AWS, or GCP)
Qualifications
Databricks Data engineer (Remote, USA)
Position Summary
We are seeking an experienced Databricks Solution Architect to join our growing healthcare analytics team. This is a full-time, remote position based in the United States. The ideal candidate will have strong hands-on experience designing and implementing scalable data solutions on Databricks and cloud platforms, with a deep understanding of healthcare data and modern data architecture.
This role is an individual contributor position responsible for solution design, technical leadership, and delivering high-quality data platforms that support analytics, reporting, and operational decision-making.
Key Responsibilities
- Design and implement scalable data solutions using Databricks Lakehouse architecture.
- Develop and optimize batch and real-time data pipelines for large-scale data processing.
- Lead technical solution design for data integration, transformation, and analytics workloads.
- Collaborate with business stakeholders, data engineers, analysts, and product teams to translate requirements into technical solutions.
- Implement data governance, security, and data quality best practices using Unity Catalog and related technologies.
- Optimize performance, reliability, and cost efficiency of Databricks workloads.
- Support data warehouse modernization and cloud migration initiatives.
- Create architecture documentation, technical standards, and design guidelines.
- Troubleshoot complex data platform issues and provide technical recommendations.
- Stay current with Databricks and cloud platform capabilities and drive adoption of best practices.
Required Qualifications
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
- Minimum 5 years of experience in data engineering, data architecture, or related technical roles.
- Hands-on experience with Databricks in enterprise environments.
- Strong knowledge of PySpark, Spark SQL, Python, and SQL.
- Experience designing and implementing Lakehouse architectures.
- Experience building scalable ETL/ELT data pipelines.
- Strong understanding of data modeling, data warehousing, and analytics platforms.
- Experience working with structured and unstructured data.
- Strong problem-solving and communication skills.
- Ability to work independently in a remote environment.
- Experience implementing data governance and security frameworks.
Preferred Qualifications
- Experience in the healthcare industry, including claims, clinical, provider, member, or revenue cycle data.
- Experience with Azure, AWS, or GCP cloud platforms.
- Exposure to machine learning and AI/ML workloads on Databricks.
Certifications
Required:
- Databricks Certified Data Engineer Associate
- Databricks Certified Data Engineer Professional
Preferred:
- Cloud platform certifications (Azure, AWS, or GCP)
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