Senior Databricks Engineer
New
E
EXLHealthcare analytics
Remote, USA; this is a full-time, remote position based in the United States.Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- Minimum 5 years of experience in data engineering, data architecture, or related technical roles.
- Required Skills
- PythonSQLDatabricksPySpark
Requirements
- Hold a bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
- Have a minimum of 5 years of experience in data engineering, data architecture, or related technical roles.
- Bring hands-on Databricks experience in enterprise environments.
- Have strong knowledge of PySpark, Spark SQL, Python, and SQL.
- Have experience designing and implementing Lakehouse architectures.
- Have experience building scalable ETL/ELT data pipelines.
- Understand data modeling, data warehousing, and analytics platforms.
- Have experience working with structured and unstructured data.
- Have experience implementing data governance and security frameworks.
- Hold Databricks Certified Data Engineer Associate and Databricks Certified Data Engineer Professional certifications.
- Healthcare data experience, including claims, clinical, provider, member, or revenue cycle data, is preferred.
- Experience with Azure, AWS, or GCP and exposure to machine learning and AI/ML workloads on Databricks are preferred.
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.
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