Senior Databricks Engineer

EXL

. Design and implement scalable data solutions using Databricks Lakehouse architecture .

Posted 9/18/2026full-timeRemote • Texas • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable data solutions using Databricks Lakehouse architecture, with a strong focus on data governance, security, and performance optimization. Proficient in developing batch and real-time data pipelines, and collaborating with cross-functional teams to deliver high-quality data platforms for analytics and decision-making.

Highest-signal resume keywords

Databricks Lakehouse ArchitecturePySparkData GovernanceDatabricks Certified Data Engineer ProfessionalCloud Platform Experience

ATS Keywords

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Hard Skills

Data EngineeringData ArchitectureETL/ELT Data PipelinesData ModelingSpark SQLPythonSQLAnalytics PlatformsStructured and Unstructured DataData Warehousing

Soft Skills

Problem-SolvingCommunicationIndependent Work

Tools & Technologies

DatabricksAzureAWSGCPUnity Catalog

Certifications & Qualifications

Databricks Certified Data Engineer AssociateDatabricks Certified Data Engineer ProfessionalCloud Platform Certifications

Industry Keywords

HealthcareClaims DataClinical DataProvider DataMember DataRevenue Cycle Data

Tech Stack

Tools & technologies

AWSAzureCloudETLGoogle Cloud PlatformPySparkPythonSparkSQLUnity

About the role

Key responsibilities & impact

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
Deliver high-quality data platforms supporting analytics, reporting, and operational decision-making

Requirements

What you’ll need

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
Required Databricks Certified Data Engineer Associate certification
Required Databricks Certified Data Engineer Professional certification
Healthcare industry experience, including claims, clinical, provider, member, or revenue cycle data, preferred
Experience with Azure, AWS, or GCP cloud platforms preferred
Exposure to machine learning and AI/ML workloads on Databricks preferred
Cloud platform certifications preferred

Benefits

Comp & perks

Full-time remote work arrangement
Individual contributor role
Opportunity to work on healthcare analytics and modern data architecture initiatives