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Databricks Data Engineer

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Hybrid

Databricks Data Engineer

EXL

Databricks Data Engineer

Skills

Google Cloud PlatformSQL QueriesData EngineeringPythonDatabricksAWSPySparkAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Noida, Uttar Pradesh, India

Work mode:

Hybrid

Published on:

26 August 2026

What they need


Description

We are looking for a Senior Databricks Data Engineer with strong expertise in Databricks, data engineering, and healthcare data. The ideal candidate will be responsible for designing scalable, secure, and high-performance data platforms supporting healthcare analytics and data integration.

The candidate should have strong knowledge of modern data architecture, Lakehouse architecture, SQL, Python, data governance, and healthcare domain workflows.

Responsibilities

  • Design and lead Databricks Lakehouse for large-scale healthcare data platforms.
  • Design data ingestion, transformation, storage, and consumption patterns using Databricks.
  • Develop Delta Lake, Unity Catalog, Databricks Workflows, and Delta Live Tables/Lakeflow.
  • Integrate data from multiple healthcare sources, including clinical, claims, eligibility, provider, and patient systems.
  • Design robust ETL/ELT pipelines using PySpark, SQL, and Databricks.
  • Establish data quality, validation, reconciliation, lineage, and governance frameworks.
  • Design secure healthcare data solutions while considering HIPAA and PHI/PII protection requirements.
  • Work with cloud platforms such as Azure, AWS, or GCP to build scalable data solutions.
  • Collaborate with data engineers, data scientists, analysts, product owners, and business stakeholders.
  • Define technical standards, architectural patterns, and best practices for Databricks development.
  • Lead performance optimization and cost-management initiatives across the Databricks platform.
  • Provide technical leadership and mentoring to data engineering teams.
  • Participate in Agile ceremonies and contribute to technical planning and roadmap discussions.

Qualifications

  • Strong hands-on experience with Databricks.
  • Expertise in Lakehouse architecture and Delta Lake.
  • Strong PySpark and SQL skills.
  • Experience with Unity Catalog and data governance.
  • Experience designing enterprise-scale data platforms.
  • Strong knowledge of ETL/ELT and data modeling.
  • Experience with cloud platforms such as Azure, AWS, or GCP.
  • Experience with data integration and orchestration tools.
  • Knowledge of CI/CD, Git, and DevOps practices.
  • Strong understanding of data security and access control.
  • Experience with Agile/Scrum methodologies.

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