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Data Warehouse Jobs (NOW HIRING)

Data Warehouse Developer

Huntsville, AL · On-site

$48.50 - $66.50/hr

Data Warehouse Developer / Data Engineer We are looking for an experienced Data Warehouse Developer / Data Engineer to design, develop, and maintain scalable enterprise data solutions with a strong ...

Cymertek Corporation is seeking a detail-oriented and innovative Data Warehouse Engineer to join their team. The role involves designing, building, and maintaining high-performance data warehousing ...

Tool support forTivoli Data Warehouse (TDW) in support of global transition in all new data centers Qualifications Tool support forTivoli Data Warehouse (TDW) in support of global transition in all ...

We specialize in developing and maintaining state-of-the-art data warehouses that support data mining, analysis, and reporting. Our team values innovation, precision, and a collaborative approach to ...

Data Warehouse Developer IDEALFORCE has a contract position available immediately for a Data Warehouse Developer to join our customer in Phoenix, Arizona. This is an ONSITE position. Our client is ...

They are seeking a Data Warehouse Engineer to design and implement enterprise-level data analysis solutions using modern data warehousing technologies. Responsibilities : • Bachelor's degree • 7 ...

Huntington Bank is looking for a data warehouse leader in our Data Technology organization. In this role you will lead a team of 12-15 dedicated to pushing the limits of continuous improvement and ...

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Data Warehouse information

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$25K

$125.9K

$171K

How much do data warehouse jobs pay per year?

As of Sep 6, 2026, the average yearly pay for data warehouse in the United States is $125,852.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,000.00 and $160,000.00 per year, depending on experience, location, and employer.

What is a data warehouse?

A data warehouse is a centralized repository designed to store, manage, and analyze large volumes of structured data from multiple sources. It enables organizations to consolidate data, making it easier to generate reports, perform analytics, and make data-driven decisions. Data warehouses are optimized for read-heavy operations and complex queries, supporting business intelligence and long-term historical analysis. They differ from traditional databases by focusing on analytical processing rather than day-to-day transaction processing.

What are the qualifications to get a data warehouse job?

The qualifications to get a data warehouse job differ by position and level of responsibility. To be a data entry worker or data clerk, you typically need a high school diploma and some technical competency, such as familiarity with spreadsheets or other simple data entry systems. To be a data warehouse architect or developer, you typically need a bachelor’s degree in information technology or computer science, and strong technical skills, including data analysis and programming in SQL and other database and server languages. Familiarity with proprietary software and hardware from companies such as Oracle is also important.

What are the key skills and qualifications needed to thrive as a data warehouse professional, and why are they important?

To excel as a Data Warehouse professional, you need a solid grasp of database design, ETL (extract, transform, load) processes, SQL, and data modeling, often supported by a degree in computer science or a related field. Familiarity with data warehouse tools such as Microsoft SQL Server, Oracle, Informatica, and cloud platforms like AWS Redshift or Google BigQuery is typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret business requirements and collaborate with stakeholders. These competencies ensure accurate, scalable data solutions that drive informed business decisions.

What are the common challenges faced by professionals working in data warehouse roles, and how can they be addressed?

Professionals in Data Warehouse roles often encounter challenges such as integrating data from diverse sources, ensuring data quality and consistency, and optimizing query performance. Addressing these issues typically involves close collaboration with data engineers, database administrators, and business analysts to establish clear data governance standards and implement robust ETL (Extract, Transform, Load) processes. Staying up to date with the latest data warehousing technologies and regularly monitoring system performance also help in overcoming these challenges, resulting in more reliable and efficient data storage and retrieval.

What is the difference between Data Warehouse vs Data Analyst?

AspectData WarehouseData Analyst
Primary RoleStores and manages large volumes of data for analysisAnalyzes data to generate insights and reports
Required SkillsDatabase management, ETL processes, SQL, data modelingData analysis, visualization, SQL, Excel
Work EnvironmentData centers, cloud platforms, IT teamsBusiness units, analytics teams, reporting tools
Common CertificationsCertified Data Management Professional (CDMP), Microsoft Certified: Data Analyst AssociateMicrosoft Certified: Data Analyst Associate, Google Data Analytics Certificate

While a Data Warehouse focuses on storing and organizing data for analysis, a Data Analyst interprets that data to provide actionable insights. Both roles often collaborate but serve different functions within data management and analysis workflows.

Is data warehouse a good career?

A career as a data warehouse professional involves designing, developing, and maintaining data storage systems that support business intelligence and analytics. It requires skills in SQL, ETL processes, and familiarity with tools like Snowflake or Redshift. The role offers strong job growth, competitive salaries, and opportunities across various industries.

What does a data warehouse do?

A data warehouse is a system used by data warehouse professionals to store, organize, and analyze large volumes of structured data from multiple sources. It enables efficient querying and reporting, supporting business intelligence and decision-making processes. Data warehouse roles often require knowledge of database tools, ETL processes, and data modeling.

What skills are needed for data warehousing?

Data warehouse professionals need strong skills in SQL, data modeling, and ETL (Extract, Transform, Load) processes. Knowledge of database management systems, data integration tools, and familiarity with cloud platforms like AWS or Azure are also important. Additionally, analytical thinking and problem-solving skills are essential for designing efficient data solutions.

What cities are hiring for Data Warehouse jobs?

Cities with the most Data Warehouse job openings:

What are the most commonly searched types of Data Warehouse jobs?

The most popular types of Data Warehouse jobs are:

What states have the most Data Warehouse jobs?

States with the most job openings for Data Warehouse jobs include:

Infographic showing various Data Warehouse job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $125,852 per year, or $60.5 per hour.

Data Warehouse Developer

Adtran

Huntsville, AL • On-site

$48.50 - $66.50/hr

Full-time

Posted 9 days ago


Job description

Welcome!

Our Growth is Creating Great Opportunities!
Our team is expanding, and we want to hire the most talented people we can. Continued success depends on it! Once you've had a chance to explore our current open positions, apply to the ones you feel suit you best and keep track of both your progress in the selection process, and new postings that might interest you!
Thanks for your interest in working on our team!

Data Warehouse Developer / Data Engineer

We are looking for an experienced Data Warehouse Developer / Data Engineer to design, develop, and maintain scalable enterprise data solutions with a strong focus on data integration, transformation pipelines, and data modelling.

This role is primarily focused on building robust and maintainable data warehouse architectures and ELT/ETL processes. The ideal candidate combines strong technical expertise in modern data platforms with the ability to understand business processes and collaborate closely with stakeholders across the organization.

You should be a self-driven and detail-oriented professional with strong analytical thinking, excellent communication skills, and the ability to translate business requirements into scalable technical solutions.

Duties and Responsibilities

  • Design, develop, optimize, and maintain enterprise-grade data warehouse solutions and data pipelines
  • Build scalable ELT/ETL processes for integrating data from various enterprise applications and source systems
  • Develop and maintain dimensional and relational data models to support analytics and operational reporting requirements
  • Ensure high standards for data quality, performance, maintainability, scalability, and reliability
  • Collaborate with business stakeholders and application teams to understand business processes, system landscapes, and data requirements
  • Support data architecture decisions and contribute to overall data platform design and best practices
  • Analyze and troubleshoot data integration and performance issues across the data platform
  • Participate in requirements gathering, technical design discussions, testing, deployment, and operational support activities
  • Create and maintain technical documentation related to data models, interfaces, and transformation logic
  • Contribute to continuous improvement initiatives around data engineering standards, automation, and development processes
  • Support reporting and analytics teams by providing reliable and well-structured data foundations

Basic Qualifications

  • Bachelor's Degree or equivalent experience required
  • 5+ years of professional experience in Data Warehouse Development, Data Engineering, or related fields
  • Strong hands-on experience with either:
    • Snowflake, or
    • Microsoft SQL Server-based Data Warehouse environments
  • Strong SQL development skills and experience optimizing complex queries and transformations
  • Solid experience in enterprise data modelling (dimensional and/or relational modelling)
  • Experience developing and maintaining ETL/ELT pipelines and integrating data from multiple business applications
  • Good understanding of enterprise business processes and the ability to work in a consulting-oriented environment with business stakeholders
  • Experience translating business requirements into technical data solutions.
  • Strong analytical, problem-solving, and troubleshooting skills
  • Excellent communication skills and ability to collaborate across technical and non-technical teams
  • Ability to work independently and manage multiple priorities in a dynamic environment

Preferred Qualifications

  • Experience with SAP ECC or Salesforce
  • Experience with Python for data processing
  • Experience with cloud-based data platforms and modern data engineering concepts
  • Experience with dbt (Data Build Tools)
  • Experience with front-end analytics and visualization tools such as:
    • Qlik
    • Tableau
  • Experience with data orchestration and scheduling tools
  • Exposure to modern analytics engineering practices and CI/CD processes for data platforms
  • Experience working in international or cross-functional project environments
  • Experience in utilizing AI technologies in displaying business data results