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Data Warehousing Engineer Jobs in Texas (NOW HIRING)

Data Engineer III

Dallas, TX · On-site

$113K - $136K/yr

Strong understanding of data warehousing concepts, including dimensional modeling, Star and ... Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Statistics ...

Sr Data Engineer

Dallas, TX · On-site

$105K - $143K/yr

Senior Data Engineer (Snowflake,DBT & DataStage) Remote W2 only We are seeking a Senior Data ... Data Warehouse Solid understanding of Data Warehouse concepts, dimensional modeling, star/snowflake ...

Data Engineer

Houston, TX · On-site

$60/hr

Data Engineer Location: Houston Tx Experience: 4-7 Years Mandatory Certification: * Databricks ... Develop and manage data warehouses, data lakes, and cloud-based data platforms. * Collaborate with ...

Associate Data Engineer

Dallas, TX · On-site

$113K - $136K/yr

Associate Data Engineer Summary: Support the development of data engineering solutions on Azure ... Data Warehousing Concepts Preferred Skills: · Exposure to Spark and Azure Data Lake. * Experience ...

Data Engineer

Plano, TX · On-site

$109K - $131K/yr

PROLIM Global Corporation is hiring a Data Engineer for one of our top clients. Location: Plano ... Design and maintain large-scale data lakes, data warehouses, and enterprise data architectures

Data Engineer

Dallas, TX · On-site

$105K - $120K/yr

Cloud Technologies • AWS (Preferred) • S3 • Lambda • Cloud-native Data Services Data EngineeringData Warehousing • ETL / ELT Development • Data Modeling • Source-to-Target Mapping ...

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

Data Engineer Location: Austin, TX or Sunnyvale, CA (Hybrid) Duration: 6 months (possibility of ... Sound knowledge of BI, Reporting and Data Warehousing. * Experience in designing and developing ETL ...

Data Engineer

Plano, TX · On-site

$70 - $75/hr

Our client is currently seeking a Data Engineer with strong experience in data modeling, data warehousing, and cloud-based data platforms. The ideal candidate will have hands-on experience with AWS ...

Data Engineer

Dallas, TX · On-site

$105K - $120K/yr

Required Technical Skills Data Platform • Snowflake • dbt (Core / Cloud) • Fivetran • SQL (Advanced) • Python Data EngineeringData Warehousing • ETL / ELT Development • Data ...

Showing results 21-40

Data Warehousing Engineer information

See Texas salary details

$80.6K

$117.9K

$149.5K

How much do data warehousing engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for data warehousing engineer in Texas is $117,854.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,700.00 and $127,200.00 per year, depending on experience, location, and employer.

What is a data warehousing engineer?

A Data Warehousing Engineer is responsible for designing, developing, and maintaining data warehouses that store and manage large volumes of structured data. They work with ETL (Extract, Transform, Load) processes to extract data from various sources, transform it into a usable format, and load it into the data warehouse. They also optimize database performance, ensure data integrity, and support business intelligence and analytics teams by providing efficient access to data. The role requires expertise in database management, SQL, ETL tools, and cloud data warehouse solutions.

What are the typical daily responsibilities of a data warehousing engineer?

As a Data Warehousing Engineer, your day often involves designing, building, and maintaining data warehouses, as well as developing ETL (extract, transform, load) processes to consolidate data from multiple sources. You'll routinely write and optimize SQL queries, monitor data quality, and troubleshoot issues to ensure smooth data flows. Collaboration with data scientists, analysts, and business stakeholders is common, as you'll help translate business needs into technical data solutions. Additionally, you may work on performance tuning, implementing data security measures, and helping to plan for future data infrastructure upgrades.

What are the key skills and qualifications needed to thrive in a data warehousing engineer position?

To thrive as a Data Warehousing Engineer, you need strong expertise in database design, ETL processes, SQL, and data modeling, typically supported by a degree in computer science or a related field. Familiarity with data warehousing tools like Informatica, Snowflake, or AWS Redshift, and certifications such as Google Cloud Data Engineer or Microsoft Azure Data Engineer, are frequently sought by employers. Analytical thinking, attention to detail, and effective communication are valuable soft skills in this role. These qualities are important for designing efficient data systems, troubleshooting complex data issues, and collaborating with cross-functional teams to ensure accurate and accessible data for decision-making.

Infographic showing various Data Warehousing Engineer job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $117,854 per year, or $56.7 per hour.

$120 - $180/hr

Other

Medical, Dental, Life, Retirement, PTO

Posted 4 days ago


Job description

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.

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.
  • 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.
  • 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.
  • Perform other functionally related duties and responsibilities as assigned.
Qualifications
  • 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.
  • 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.
  • 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.
  • Experience working with large datasets, data cleansing, data transformation, reporting, statistical analysis, and advanced analytics.
  • Exceptional verbal and written communication skills, with the ability to communicate effectively with technical and non‑technical stakeholders, lead requirements gathering sessions, produce technical documentation, and present solutions to leadership audiences.
  • Proven ability to work independently while collaborating effectively in a fast‑paced, team‑oriented environment.
  • Strong commitment to continuous learning, innovation, and staying current with emerging cloud, data engineering, AI, and analytics technologies.

Preferred:

  • 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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What We Offer

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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