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Senior Databricks Engineers

EXL · Business Process Outsourcing (BPO) · AI Consulting & Integration · Certification required · Bachelor's Degree · Python · SQL · ETL/ELT · 1 month ago

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Salary

≈ $103k – $187k per year (Estimated)

Location

Remote (United States)

Seniority

Senior · 5+ years exp

Visa

H-1B filings in 12 months: 281 · for this role: 125 · green card filings: 17

Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Sep 18, 2026. EXL scores B on the Alion truth index.

Overview

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Impact

Profile match

EXL

EXL, legally ExlService Holdings, is a data analytics, AI and digital operations company headquartered in New York that runs outsourced business processes and builds data and AI solutions for insurers, healthcare organisations, banks, media and retail companies. Founded in 1999 and listed on Nasdaq, it has more than 60,000 employees across six continents, with large delivery centers in Noida, Gurgaon, Pune, Bengaluru and Chennai and a newer AI hub in Dublin. It hires data scientists and data engineers, GenAI and MLOps engineers, analytics managers, solution consultants and client partners, plus talent acquisition, finance and medical coding staff.

exlservice.com · HQ: New York, United States · AI Consulting & Integration · Analytics & BI Consulting · Business Process Outsourcing (BPO) · 5000+ employees · Est. 1999

Tech stack of EXL

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)

Databricks Data engineer (Remote, USA)

Position Summary

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)

Databricks Data engineer (Remote, USA)

Position Summary

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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