Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Dallas, TX
Live, first seen by us 83 days agoEmployment type in the employer’s posting: FULL_TIMEFrom the employer’s posting
Design and maintain cloud ETL/ELT pipelines on Azure Databricks, Synapse and Data Factory
Tune complex SQL, T-SQL, Spark SQL and PySpark workloads for performance and cost
Build and document Databricks notebooks, APIs and data pipelines with CI/CD and Azure DevOps
Manage data projects end to end, from requirements through deployment and production support
Build curated datasets and feature engineering pipelines for AI and machine learning
Design, develop, and maintain scalable cloud-based data engineering solutions, including ETL/ELT pipelines
Develop, optimize, and troubleshoot complex SQL, T-SQL, Spark SQL, and PySpark workloads, with a strong focus on performance tuning, scalability, reliability, and cost efficiency.
Design, code, test, tune, deploy, and document new and existing data solutions, including Databricks notebooks developed in Python, PySpark, Spark SQL, and Scala
Manage the complete development lifecycle for complex, high-impact data initiatives, including requirements gathering, solution design, development, testing, deployment, production support, and continuous improvement.
Support and enable AI, machine learning, and Generative AI initiatives by developing curated datasets, feature engineering pipelines, and scalable data platforms
7+ years of experience in cloud data engineering, ETL/ELT development, data warehousing, and enterprise analytics solutions.
Experience in the Property & Casualty Insurance, Financial Services, Accounting, or Actuarial domains.
Proven experience implementing the Medallion Architecture (Bronze, Silver, and Gold layers) to support scalable, governed, and high-quality data pipelines for enterprise analytics and reporting.
Proven experience designing, developing, and tuning complex queries and large-scale data processing solutions across high-volume datasets.
Experience implementing CI/CD pipelines, Git-based source control, Azure DevOps, and automated deployment frameworks.
Strong understanding of data warehousing concepts, including dimensional modeling, Star and Snowflake schemas, data governance, metadata management, and data quality best practices.
- Experience supporting AI, Machine Learning, and Generative AI initiatives, including data preparation, feature engineering, model integration, vectorized data architectures, and MLOps processes. - Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Statistics, or a related technical discipline, or equivalent work experience. - Strong analytical and problem-solving skills with a demonstrated ability to design innovative solutions for complex business and technical challenges.
From the employer’s 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 2,133 postings in the last year. Stated ranges, not salaries paid.
Day 83
Up longer than most. Similar jobs usually come down between day 6 and day 54.
Well past AmTrust Financial Services’s usual: its jobs come down by about day 27.
From 11,069 similar postings that came down, and 11 of AmTrust Financial Services’s. Coming down is not always a hire.
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add 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.
Overview AmTrust is seeking a highly motivated and accomplished Cloud Data Engineer with expertise in Azure Databricks, Azure Synapse Analytics, SQL, and cloud-based data platforms. The ideal candidate will have experience designing, developing, and optimizing scalable data lakehouse and data warehousing solutions that support enterprise reporting, analytics, and business intelligence. Strong technical skills in Python, PySpark, SQL, T-SQL, and Scala are required, along with experience building high-volume ETL/ELT pipelines, developing highly scalable and reusable Databricks notebooks, and leveraging Azure DevOps, Git, CI/CD, and cloud automation best practices to deliver secure and efficient data solutions. The successful candidate will also support AI and machine learning initiatives, including data preparation, feature engineering, Generative AI integrations, and MLOps processes.
- Develop, optimize, and troubleshoot complex SQL, T-SQL, Spark SQL, and PySpark workloads, with a strong focus on performance tuning, scalability, reliability, and cost efficiency. - Design, code, test, tune, deploy, and document new and existing data solutions, including Databricks notebooks developed in Python, PySpark, Spark SQL, and Scala, as well as cloud-native applications, APIs, and data pipelines utilizing Git, CI/CD, and Azure DevOps best practices. - Manage the complete development lifecycle for complex, high-impact data initiatives, including requirements gathering, solution design, development, testing, deployment, production support, and continuous improvement.
- Proven experience implementing the Medallion Architecture (Bronze, Silver, and Gold layers) to support scalable, governed, and high-quality data pipelines for enterprise analytics and reporting. - Advanced proficiency in Python, PySpark, Spark SQL, SQL, T-SQL, and Scala, with the ability to develop, optimize, and support highly scalable Databricks notebooks and distributed data processing workloads. - Proven experience designing, developing, and tuning complex queries and large-scale data processing solutions across high-volume datasets.
Responsibilities - Design, develop, and maintain scalable cloud-based data engineering solutions, including ETL/ELT pipelines, data integration processes, reports, and analytics workflows using technologies such as Azure Databricks, Azure Synapse Analytics, Azure Data Factory, and SQL. - Demonstrate expert knowledge of modern cloud architecture, data lakehouse design, and data warehousing best practices, evaluating technical design alternatives and their business and operational impacts.
- Demonstrate expert knowledge of modern cloud architecture, data lakehouse design, and data warehousing best practices, evaluating technical design alternatives and their business and operational impacts. - Develop, optimize, and troubleshoot complex SQL, T-SQL, Spark SQL, and PySpark workloads, with a strong focus on performance tuning, scalability, reliability, and cost efficiency. - Design, code, test, tune, deploy, and document new and existing data solutions, including Databricks notebooks developed in Python, PySpark, Spark SQL, and Scala, as well as cloud-native applications, APIs, and data pipelines utilizing Git, CI/CD, and Azure DevOps best practices.
- Support and enable AI, machine learning, and Generative AI initiatives by developing curated datasets, feature engineering pipelines, and scalable data platforms that power advanced analytics and intelligent business solutions. - Stay current with emerging trends and technologies in cloud computing, data engineering, artificial intelligence, Databricks, Azure services, automation, and analytics, recommending innovative solutions that drive business value and operational excellence. - Collaborate effectively with business stakeholders, architects, developers, and leadership teams, leveraging exceptional verbal and written communication skills to translate business requirements into scalable technical solutions and communicate complex concepts to both technical and non-technical audiences.
- 7+ years of experience in cloud data engineering, ETL/ELT development, data warehousing, and enterprise analytics solutions. - Strong hands-on experience with Azure Databricks, Azure Synapse Analytics, Azure Data Factory, and modern cloud-based data lakehouse architectures. - Proven experience implementing the Medallion Architecture (Bronze, Silver, and Gold layers) to support scalable, governed, and high-quality data pipelines for enterprise analytics and reporting.
- Proven experience designing, developing, and tuning complex queries and large-scale data processing solutions across high-volume datasets. - Experience implementing CI/CD pipelines, Git-based source control, Azure DevOps, and automated deployment frameworks. - Strong understanding of data warehousing concepts, including dimensional modeling, Star and Snowflake schemas, data governance, metadata management, and data quality best practices.
- Experience in the Property & Casualty Insurance, Financial Services, Accounting, or Actuarial domains. - Microsoft certifications such as Azure Data Engineer Associate (DP-203), Azure AI Engineer Associate, Databricks Data Engineer Associate/Professional, or related cloud certifications. This job description is designed to provide a general overview of the requirements of the job and does not entail a comprehensive listing of all activities, duties, or responsibilities that will be required in this position.
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New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 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.
AmTrust is seeking a highly motivated and accomplished Cloud Data Engineer with expertise in Azure Databricks, Azure Synapse Analytics, SQL, and cloud-based data platforms. The ideal candidate will have experience designing, developing, and optimizing scalable data lakehouse and data warehousing solutions that support enterprise reporting, analytics, and business intelligence. Strong technical skills in Python, PySpark, SQL, T-SQL, and Scala are required, along with experience building high-volume ETL/ELT pipelines, developing highly scalable and reusable Databricks notebooks, and leveraging Azure DevOps, Git, CI/CD, and cloud automation best practices to deliver secure and efficient data solutions.
The successful candidate will also support AI and machine learning initiatives, including data preparation, feature engineering, Generative AI integrations, and MLOps processes.
Preferred:
This job description is designed to provide a general overview of the requirements of the job and does not entail a comprehensive listing of all activities, duties, or responsibilities that will be required in this position.
#LI-BL1
AmTrust Financial Services offers a competitive compensation package and excellent career advancement opportunities. Our benefits include Medical & Dental Plans, Life Insurance, including eligible spouses & children, Health Care Flexible Spending, Dependent Care, 401k Savings Plans, Paid Time Off.
AmTrust strives to create a diverse and inclusive culture where thoughts and ideas of all employees are appreciated and respected. This concept encompasses but is not limited to human differences with regard to race, ethnicity, gender, sexual orientation, culture, religion or disabilities.
AmTrust values excellence and recognizes that by embracing the diverse backgrounds, skills, and perspectives of its workforce, it will sustain a competitive advantage and remain an employer of choice. Diversity is a business imperative, enabling us to attract, retain and develop the best talent available. We see diversity as more than just policies and practices. It is an integral part of who we are as a company, how we operate and how we see our future.
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Dallas, TX
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