Senior Databricks Engineers

Job Description: 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)