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Data Warehouse Engineer Jobs in Dallas, TX (NOW HIRING)

Expert Technical Solutions

Data Warehouse Developer

Irving, TX · On-site

$47.25 - $64.75/hr

Senior Data Warehouse Engineer Location: Irving, TX (Onsite 5 Days/Week) Employment Type: Contract-to-Hire (4-6 Months) Work Authorization: Must be authorized to work in the U.S. without sponsorship ...

RIT Solutions, Inc.

Data warehouse Developer

Plano, TX · On-site

$47.50 - $65/hr

RIT Solutions, Inc. is a company seeking a Data Warehouse Developer. The primary responsibilities include developing and maintaining data pipelines using various technologies such as Python, SQL, and ...

TMS

Senior Software Engineer, Data Warehousing

Irving, TX · On-site

$117K - $155K/yr

Irving, TX- Hybrid Job Summary The Senior Data Warehouse Engineer is responsible for designing, building, and optimizing enterprise data pipelines and data models to transform complex operational ...

American Heart Association

Data Warehouse Developer

Dallas, TX · On-site

$45.25 - $62/hr

The American Heart Association has an excellent opportunity for a Data Warehouse Developer ! This position can be home-based. This is a full-time, benefits-eligible, grant-funded opportunity. Current ...

American Heart Association

Data Warehouse Developer

Dallas, TX · On-site +1

$45.25 - $62/hr

The American Heart Association has an excellent opportunity for a Data Warehouse Developer ! This position can be home-based. This is a full-time, benefits-eligible, grant-funded opportunity. Current ...

American Heart Association

Data Warehouse Developer

Dallas, TX · On-site +1

$48.75 - $66.75/hr

The American Heart Association has an excellent opportunity for a Data Warehouse Developer ! This position can be home-based. This is a full-time, benefits-eligible, grant-funded opportunity. Current ...

PROLIM Global Corporation

Data Modeller

Plano, TX · On-site

Data Warehouse Developer / Data Modeler Location: San Antonio/Plano Job Summary We are seeking an experienced Data Warehouse Developer / Data Modeler with a strong background in data architecture ...

Jobtailor

Software Engineer - Data Insights

Irving, TX · On-site

$110 - $150/hr

* Design, build, and support scalable data warehouse solutions and data pipelines using Snowflake and ... Partner with engineers, analysts, product teams, architects, and business stakeholders to deliver ...

APN Consulting, Inc.

Data Engineer

Dallas, TX · On-site

$113K - $136K/yr

They are seeking a Data Engineer to work with Snowflake cloud data platform and build data warehouse solutions, requiring a strong background in data processing and pipeline development.

McKesson

Software Engineer- Data Insights

Irving, TX · On-site

$106K - $176K/yr

Optimize data warehouse performance through query tuning, efficient data architecture, and platform ... Partner with engineers, analysts, and business stakeholders to deliver well-documented data ...

McKesson

Software Engineer- Data Insights

Irving, TX · On-site

$106K - $176K/yr

Optimize data warehouse performance through query tuning, efficient data architecture, and platform ... Partner with engineers, analysts, and business stakeholders to deliver well-documented data ...

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Showing results 1-20

All JobsData Warehouse Engineer JobsData Warehouse Engineer Jobs in Dallas, TX

Data Warehouse Engineer information

See Dallas, TX salary details

$85.6K

$125.1K

$158.8K

How much do data warehouse engineer jobs pay per year?

As of Sep 1, 2026, the average yearly pay for data warehouse engineer in Dallas, TX is $125,137.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,300.00 and $135,000.00 per year, depending on experience, location, and employer.

What is a data warehouse engineer?

Data Warehouse Engineers are IT professionals who design, build, and maintain systems used for storing and analyzing large volumes of data. They create data models, implement ETL (Extract, Transform, Load) processes, and ensure data integrity and optimized performance within the data warehouse environment. Their work enables organizations to efficiently store data from various sources and make it accessible for business intelligence and analytics. Data Warehouse Engineers often collaborate with data analysts, data scientists, and database administrators to support informed decision-making.

What are the key skills and qualifications needed to thrive as a data warehouse engineer?

To thrive as a Data Warehouse Engineer, you need expertise in database design, ETL processes, SQL, and data modeling, typically supported by a degree in computer science or a related field. Familiarity with tools like Microsoft SQL Server, Oracle, Informatica, and cloud platforms such as AWS Redshift or Google BigQuery, as well as certifications in these technologies, are valuable. Strong problem-solving abilities, attention to detail, and effective communication help you collaborate with stakeholders and address data challenges efficiently. These skills ensure the reliable integration, storage, and retrieval of high-quality data, which is critical for business intelligence and decision-making.

What are some common challenges data warehouse engineers face when integrating data from multiple sources?

Data Warehouse Engineers often encounter challenges such as data inconsistency, varying data formats, and incomplete or duplicate records when integrating information from diverse systems. Addressing these issues requires careful planning, robust ETL (Extract, Transform, Load) processes, and close collaboration with source system owners and data analysts. Additionally, ensuring data quality and maintaining up-to-date documentation are crucial to support efficient troubleshooting and future scalability.

What is the difference between Data Warehouse Engineer vs Data Analyst?

AspectData Warehouse EngineerData Analyst
CredentialsBachelor's in CS, Data Science, or related; certifications like AWS, Google CloudBachelor's in Statistics, Math, or related; certifications like Microsoft Data Analyst
Work EnvironmentDesigning, building, maintaining data warehouses; working with ETL toolsAnalyzing data, creating reports, visualizations
Industry UsageUsed in organizations managing large-scale data infrastructureUsed across industries for business insights and decision-making

While both roles work with data, Data Warehouse Engineers focus on building and maintaining data storage systems, whereas Data Analysts interpret data to generate insights. They often collaborate but have distinct technical and functional responsibilities.

What does a data warehouse engineer do?

A data warehouse engineer designs, develops, and maintains data storage systems that aggregate and organize large volumes of data from various sources. They use tools like SQL, ETL processes, and data modeling to ensure data is accessible, accurate, and optimized for analysis. Their work supports business intelligence and decision-making processes.

What are popular job titles related to Data Warehouse Engineer jobs in Dallas, TX?

For Data Warehouse Engineer jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Data Warehouse Engineer jobs in Dallas, TX look for?

The top searched job categories for Data Warehouse Engineer jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Data Warehouse Engineer jobs?

Cities near Dallas, TX with the most Data Warehouse Engineer job openings:

Data Warehouse Engineer jobs near you
Infographic showing various Data Warehouse Engineer job openings in Dallas, TX as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $125,137 per year, or $60.2 per hour.

Data Warehouse Developer

Expert Technical Solutions

Irving, TX • On-site

$47.25 - $64.75/hr

Contractor

Re-posted 11 days ago

Job description

Senior Data Warehouse Engineer
Location: Irving, TX (Onsite 5 Days/Week)
Employment Type: Contract-to-Hire (4–6 Months)
Work Authorization: Must be authorized to work in the U.S. without sponsorship
Position Overview
Our client is a Fortune 500 Insurance company seeking a highly technical Senior Data Warehouse Engineer to help modernize and scale a large enterprise data environment supporting critical operational and supply chain functions. This individual will play a key role in designing and implementing a long-term data strategy that reduces reliance on transactional systems while improving data availability, reporting performance, and scalability.
The ideal candidate will have deep expertise across Oracle, SQL Server/Azure SQL, Snowflake, and Azure Data Factory, with the ability to architect efficient data movement and transformation processes for large, complex datasets. This role requires someone who can move beyond simply building pipelines and instead understand source system architecture, optimize data structures, and design scalable warehouse solutions capable of supporting enterprise analytics and reporting.
This is a hands-on engineering position for someone who enjoys solving complex data challenges, optimizing performance, and building modern data platforms that support long-term business growth.
Key Technologies
  • Azure Data Factory (ADF)
  • Azure SQL Database / SQL Server
  • Oracle PL/SQL
  • Snowflake
  • JSON Data Processing
  • REST APIs
  • Data Warehousing
  • Data Modeling
  • Power BI
Primary Responsibilities
  • Design, develop, and maintain scalable data pipelines using Azure Data Factory.
  • Build and optimize enterprise data warehouse solutions supporting operational reporting and analytics.
  • Design and implement incremental data loading strategies utilizing UPSERT, MERGE, CDC, and other efficient synchronization techniques.
  • Extract, transform, and load data from large-scale Oracle environments into Azure SQL and Snowflake platforms.
  • Analyze complex source systems and identify optimal approaches for data extraction, transformation, and storage.
  • Design and maintain dimensional data models, including star and snowflake schemas.
  • Transform semi-structured data, including complex JSON payloads, into consumable relational datasets.
  • Develop data integration solutions leveraging REST APIs, sFTP-based workflows, and other external data sources.
  • Improve query performance through indexing strategies, partitioning, optimization, and database tuning.
  • Establish data engineering standards, best practices, naming conventions, and architectural guidelines.
  • Collaborate closely with business intelligence and reporting teams to ensure data accuracy, consistency, and performance.
  • Troubleshoot and resolve issues across ingestion, transformation, storage, and reporting layers.
  • Mentor team members and provide technical leadership on data engineering best practices.
Required Qualifications
  • 8+ years of experience in Data Engineering, Data Warehousing, or related disciplines.
  • Advanced SQL expertise across Oracle, SQL Server/Azure SQL, and Snowflake.
  • Strong hands-on experience developing and supporting Azure Data Factory solutions.
  • Demonstrated experience working within large-scale enterprise data environments.
  • Deep understanding of incremental data processing methodologies, including UPSERT and MERGE patterns.
  • Strong Oracle PL/SQL development experience.
  • Experience designing and optimizing large-scale relational databases.
  • Proven ability to tune complex SQL queries and optimize database performance.
  • Experience working with JSON and other semi-structured data formats.
  • Experience integrating data from ERP systems, operational platforms, APIs, and external file-based sources.
  • Strong understanding of dimensional modeling concepts and enterprise data warehouse design.
  • Ability to evaluate source system structures and design efficient downstream data architectures.
Preferred Qualifications
  • Experience supporting supply chain, logistics, manufacturing, or operational data environments.
  • Experience working with large ERP platforms such as Oracle EBS or similar enterprise systems.
  • Experience implementing enterprise data modernization initiatives.
  • Exposure to Power BI and enterprise reporting solutions.
  • Experience with data governance, data quality, and master data management initiatives.
What Success Looks Like
  • Reduce reporting dependency on transactional production systems.
  • Improve reporting reliability and performance through optimized warehouse architecture.
  • Implement scalable incremental data ingestion and synchronization processes.
  • Create sustainable, maintainable data structures that support long-term business growth.
  • Establish engineering best practices that improve efficiency, consistency, and scalability across the data platform.