Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
United States
Actively hiring, first seen by us 22 hours agoDesign and develop scalable data pipelines using Azure Databricks, PySpark, Spark SQL, and Python.
Build and maintain ETL/ELT pipelines for batch and large-scale data processing.
Develop data ingestion and transformation workflows using Azure Data Factory (ADF).
Key Responsibilities Design and develop scalable data pipelines using Azure Databricks, PySpark, Spark SQL, and Python. Build and maintain ETL/ELT pipelines for batch and large-scale data processing.
Design and develop scalable data pipelines using Azure Databricks, PySpark, Spark SQL, and Python. Build and maintain ETL/ELT pipelines for batch and large-scale data processing. Develop data ingestion and transformation workflows using Azure Data Factory (ADF).
Build and maintain ETL/ELT pipelines for batch and large-scale data processing. Develop data ingestion and transformation workflows using Azure Data Factory (ADF). Design and implement Delta Lake / Lakehouse solutions.
9+ years of overall Data Engineering experience.
strong hands-on experience with Azure Databricks, Apache Spark, PySpark, SQL, Delta Lake, and Azure Data Factory (ADF)
4+years of hands-on Databricks/Spark experience preferred.
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
Day 0
Early. Similar jobs usually come down between day 6 and day 56.
From 13,754 similar postings that came down. Coming down is not always a hire.
370 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Key Responsibilities - Design and develop scalable data pipelines using Azure Databricks, PySpark, Spark SQL, and Python. - Build and maintain ETL/ELT pipelines for batch and large-scale data processing.
Primary Skill: Azure Databricks / Data Engineering Secondary Skills: PySpark, SQL, Python, Azure Data Factory, Delta Lake, ADLS Gen2
Job Description We are looking for an experienced Databricks Data Engineer to design, develop, and maintain scalable data engineering solutions on the Azure cloud platform. The candidate should have strong hands-on experience with Azure Databricks, Apache Spark, PySpark, SQL, Delta Lake, and Azure Data Factory (ADF), with a solid understanding of modern data lakehouse architectures. Key Responsibilities
- Work with Azure Data Lake Storage Gen2 (ADLS Gen2) for data ingestion, storage, and processing. - Develop optimized PySpark and SQL transformations for large datasets. - Implement Delta tables, schema management, data quality checks, and performance optimization.
Good to Have - Databricks SQL - Structured Streaming
- Build and maintain ETL/ELT pipelines for batch and large-scale data processing. - Develop data ingestion and transformation workflows using Azure Data Factory (ADF). - Design and implement Delta Lake / Lakehouse solutions.
- Design and implement Delta Lake / Lakehouse solutions. - Work with Azure Data Lake Storage Gen2 (ADLS Gen2) for data ingestion, storage, and processing. - Develop optimized PySpark and SQL transformations for large datasets.
- Monitor pipelines, troubleshoot failures, and optimize Spark workloads. - Implement CI/CD processes using Azure DevOps and Git. - Collaborate with Data Architects, Data Analysts, BI teams, and business stakeholders.
- 4+years of hands-on Databricks/Spark experience preferred. - Experience delivering cloud-based data platforms on Microsoft Azure. Other Requirements
Other Requirements Primary Skill: Azure Databricks / Data Engineering Secondary Skills: PySpark, SQL, Python, Azure Data Factory, Delta Lake, ADLS Gen2
- Implement Delta tables, schema management, data quality checks, and performance optimization. - Work with Databricks Workflows/Jobs for pipeline orchestration and scheduling. - Implement data governance and access controls using Unity Catalog.
- 9+ years of overall Data Engineering experience. - 4+years of hands-on Databricks/Spark experience preferred. - Experience delivering cloud-based data platforms on Microsoft Azure.
- Develop data ingestion and transformation workflows using Azure Data Factory (ADF). - Design and implement Delta Lake / Lakehouse solutions. - Work with Azure Data Lake Storage Gen2 (ADLS Gen2) for data ingestion, storage, and processing.
- Develop optimized PySpark and SQL transformations for large datasets. - Implement Delta tables, schema management, data quality checks, and performance optimization. - Work with Databricks Workflows/Jobs for pipeline orchestration and scheduling.
- Structured Streaming - Kafka or Event Hubs - Power BI
- Collaborate with Data Architects, Data Analysts, BI teams, and business stakeholders. - Support downstream reporting and analytics solutions such as Power BI. Key Responsibilities
- Kafka or Event Hubs - Power BI - Terraform
- Power BI - Terraform - CI/CD automation
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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.
We are looking for an experienced Databricks Data Engineer to design, develop, and maintain scalable data engineering solutions on the Azure cloud platform. The candidate should have strong hands-on experience with Azure Databricks, Apache Spark, PySpark, SQL, Delta Lake, and Azure Data Factory (ADF), with a solid understanding of modern data lakehouse architectures.
Primary Skill: Azure Databricks / Data Engineering
Secondary Skills: PySpark, SQL, Python, Azure Data Factory, Delta Lake, ADLS Gen2
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United States
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