Noida, Uttar Pradesh, India
Open 3 months, first seen by us 93 days agoWork setup in the employer’s posting: HybridFrom the employer’s posting
Design and build scalable data pipelines in Azure Databricks using PySpark and Spark SQL
Orchestrate ETL/ELT workflows with Azure Data Factory and Databricks Workflows
Maintain CI/CD pipelines that promote Databricks code across dev, test and prod
Develop and maintain healthcare data models, entities and data flows
Build enterprise BI architectures, data warehouses and data marts
Design, develop, test, and deploy robust and scalable data pipelines using Azure Databricks, PySpark, and Spark SQL
Implement workflow orchestration using Azure Data Factory and Databricks Workflows to automate ETL/ELT processes.
Implement and maintain CI/CD pipelines for Databricks notebooks, scripts, and configurations
Develop and maintain healthcare data models, including data entities, relationships, and data flows
Design and implement enterprise-wide BI architectures. Develop and maintain data warehouses and data marts.
Open 3 monthsWe first saw this posting 93 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 93
Up longer than most. Similar jobs usually come down between day 6 and day 56.
Well past EXL Service’s usual: its jobs come down by about day 21.
From 13,630 similar postings that came down, and 281 of EXL Service’s. Coming down is not always a hire.
211 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Strong experience with core Azure data services – Azure Data Lake Storage (Gen 2), Azure data factory. - Proficiency in Python and expert-level skills in SQL - Solid understanding of data warehousing concepts, dimensional modeling (star/snowflake schemas), and data architecture principles
Responsibilities - Design, develop, test, and deploy robust and scalable data pipelines using Azure Databricks, PySpark, and Spark SQL for processing large volumes of structured and unstructured data. - Implement workflow orchestration using Azure Data Factory and Databricks Workflows to automate ETL/ELT processes.
Role Title: Azure Data Engineer BU/Segment: Healthcare Analytics
- Design, develop, test, and deploy robust and scalable data pipelines using Azure Databricks, PySpark, and Spark SQL for processing large volumes of structured and unstructured data. - Implement workflow orchestration using Azure Data Factory and Databricks Workflows to automate ETL/ELT processes. - Implement and maintain CI/CD pipelines for Databricks notebooks, scripts, and configurations using Azure DevOps or GitHub Actions, promoting code across dev, test, and prod environments.
- Implement workflow orchestration using Azure Data Factory and Databricks Workflows to automate ETL/ELT processes. - Implement and maintain CI/CD pipelines for Databricks notebooks, scripts, and configurations using Azure DevOps or GitHub Actions, promoting code across dev, test, and prod environments. - Develop and maintain healthcare data models, including data entities, relationships, and data flows, to support healthcare analytics and decision-making.
- 6+ years of experience as a Data Engineer with a proven track record of building data pipelines in the cloud. - 3+ years of hands-on experience with Azure Databricks - Strong experience with core Azure data services – Azure Data Lake Storage (Gen 2), Azure data factory.
- 3+ years of hands-on experience with Azure Databricks - Strong experience with core Azure data services – Azure Data Lake Storage (Gen 2), Azure data factory. - Proficiency in Python and expert-level skills in SQL
- Solid understanding of data warehousing concepts, dimensional modeling (star/snowflake schemas), and data architecture principles - Experience with CI/CD pipelines (Azure DevOps, Jenkins, GitHub Actions) and version control systems (Git). - Demonstrated experience and knowledge of strategic problem solving and frameworks, and project management skills
- Excellent written and verbal communication with the ability to establish credibility and strong relationships with stakeholders Role Title: Azure Data Engineer BU/Segment: Healthcare Analytics
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Role Title: Azure Data Engineer
BU/Segment: Healthcare Analytics
Responsibilities
Person attributes
Role Title: Azure Data Engineer
BU/Segment: Healthcare Analytics
Responsibilities
Person attributes
Role Title: Azure Data Engineer
BU/Segment: Healthcare Analytics
Responsibilities
Person attributes
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Noida, Uttar Pradesh, India
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