Databricks Engineer

• Build and maintain batch and streaming data pipelines for extracting, transforming, and loading (ETL/ELT) data from multiple sources into the Databricks lakehouse on Azure.
• Implement data ingestion using Auto Loader, Lakeflow Connect, and Azure Data Factory.
• Develop pipelines with Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables), including data quality expectations.
• Perform data manipulation and transformation using PySpark and Spark SQL, ensuring data is prepared for analytics and reporting.
• Configure, schedule, and monitor data workflows with Lakeflow Jobs (formerly Databricks Workflows).
• Implement data models within the lakehouse following medallion architecture (bronze/silver/gold) and team modeling standards.
• Apply Unity Catalog permissions and governance standards to the data assets you build.
• Write unit and data quality tests and deploy pipelines through CI/CD using Git folders and Declarative Automation Bundles (formerly Databricks Asset Bundles).
• Monitor, troubleshoot, and resolve pipeline failures and data quality issues in production.
• Participate in code reviews and contribute to team documentation and engineering standards.
• Collaborate with cross-functional teams, including business stakeholders and IT, to ensure data solutions meet business and performance requirements aligned to project goals.

• 6+ years of professional experience in data engineering, data & analytics or data warehousing.
• 3+ years of hands-on experience working with Databricks in a data engineering capacity.
• 3+ years of experience with Python, including manipulating large datasets using PySpark DataFrames, Spark SQL, and/or the pandas API on Spark.
• 2+ years of data engineering experience on Microsoft Azure (e.g., ADLS Gen2, Azure Data Factory, Key Vault).

Skills and Knowledge

• Proficiency in Python programming for data engineering tasks.
• Strong knowledge of SQL for data modeling, transformation, and querying.
• Working knowledge of Delta Lake fundamentals (e.g., MERGE, schema evolution, time travel).
• Working knowledge of Unity Catalog concepts, including catalogs, schemas, and permissions.
• Experience with Git-based version control and familiarity with CI/CD practices for data pipelines.
• Understanding of testing and deployment strategies for data pipelines, including productionizing ETL pipelines and Databricks SQL queries.

Education

• Bachelor's degree in computer science, Information Systems, Data Engineering, or a closely related field, or equivalent professional experience.

• Experience implementing streaming data ingestion in Databricks (Structured Streaming, Auto Loader, Event Hubs).
• Experience with healthcare data (e.g., claims, EHR/clinical data, HL7/FHIR) and HIPAA/PHI handling.
• Exposure to Spark and Delta Lake performance tuning and compute cost optimization.
• Familiarity with dimensional modeling and SCD Type 1 and Type 2 patterns.
• Experience enabling BI consumption through Databricks SQL warehouses and tools such as Power BI.

The base salary for this position is $92,250 to $120,000 plus incentives that align with individual and company performance. Actual salaries will vary based on work location, qualifications, skills, education, experience, and competencies. Benefits available to eligible employees in this role include medical, dental, and vision insurance, comprehensive employee assistance program, 401(k) retirement plan, paid time off and holidays and paid learning days.

We accept applications for this position on an ongoing basis. It is currently for an existing, immediate vacancy; however, we are also considering applications for future opportunities as they arise. We encourage all interested candidates to apply.

As part of the hiring process, candidates may be required to undergo background screening and identity verification, where permitted by applicable law and consistent with the requirements of the role. Certain verification processes used by the Company or its service providers may involve technologies that rely on biometric identifiers or biometric information, where permitted by law. If biometric identifiers or biometric information are collected, used, or stored, the Company will provide the legally required disclosures and obtain any required written consent prior to such collection, and will handle such information in accordance with applicable biometric privacy laws and Company policies.