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Cloud Data Warehouse Jobs (NOW HIRING)

challenger

Data Warehouse Analytics Specialist

Sandy, UT

$17 - $21.75/hr

Experience with Snowflake or similar cloud data warehouse platforms. * Business intelligence or reporting experience. * Experience documenting business rules, metrics, or data definitions.

challenger

Data Warehouse Analytics Specialist

Sandy, UT

$17 - $21.75/hr

Experience with Snowflake or similar cloud data warehouse platforms. * Business intelligence or reporting experience. * Experience documenting business rules, metrics, or data definitions.

Bayforce

Data Warehouse Engineer

Detroit, MI

Data Warehouse Engineer Employment Type: Contract Duration: 6 month contract, with potential ... The ideal candidate will have hands-on experience with modern cloud data technologies, strong data ...

TechNix LLC

Cloud Data Architect

West Sacramento, CA

$67.50 - $85.75/hr

The candidate shall have advanced expertise in AI technologies, data warehouse, cloud platforms, data engineering, machine learning, and integration best practices, and will act as a trusted ...

New

Zortech Solutions

Azure Data Engineer

Iselin, NJ · On-site

$116K - $139K/yr

This position is for a Cloud Data engineer with a background in Python, Pyspark, SQL and data warehousing for enterprise level systems. The position calls for someone that is comfortable working with ...

Terumo Corporation

Cloud Data Architect

Somerset, NJ · On-site

$67.25 - $86.75/hr

Define target-state architectures and phased migration strategies using Databricks, Lakehouse, and cloud data warehouse pattern * Provide architectural leadership for migration and modernization ...

University of Rochester

$86K - $129K/yr

The Senior Data Warehouse Developer is responsible for architecting, designing, developing ... Architects data integration and transformation processes across on premise and cloud data sources.

IT

Cloud Data Architect

Somerset, NJ

$67.25 - $86.75/hr

Define target-state architectures and phased migration strategies using Databricks, Lakehouse, and cloud data warehouse pattern * Provide architectural leadership for migration and modernization ...

Intraedge

Google Cloud Platform Data Engineer

Phoenix, AZ · Hybrid

$113K - $136K/yr

Phoenix, AZ Duration: Long Term Contract Expert in SQL and Data warehousing concepts. Hands-on experience with public cloud data warehouse (Google Cloud Platform, Azure, AWS). Google Cloud Platform ...

Intraedge

Google Cloud Platform Data Engineer

Austin, TX · Hybrid

$113K - $136K/yr

Austin, TX Duration: Long Term Contract Expert in SQL and Data warehousing concepts. Hands-on experience with public cloud data warehouse (Google Cloud Platform, Azure, AWS). Google Cloud Platform ...

Terumo Corporation

Cloud Data Architect

Somerset, NJ · On-site

$67.25 - $86.75/hr

Define target-state architectures and phased migration strategies using Databricks, Lakehouse, and cloud data warehouse pattern * Provide architectural leadership for migration and modernization ...

Amway

Cloud Data Engineer

Ada, MI · On-site

$112K - $134K/yr

Responsibilities : • Designing, building, and maintaining ETL/ELT data pipelines using Python and SQL • Migrating legacy on‑premise data warehouses and BI datasets to cloud platforms • ...

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Cloud Data Warehouse information

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How much do cloud data warehouse jobs pay per hour?

As of Jun 17, 2026, the average hourly pay for cloud data warehouse in the United States is $61.71, according to ZipRecruiter salary data. Most workers in this role earn between $54.09 and $74.04 per hour, depending on experience, location, and employer.

Is SQL Server a DWH?

SQL Server is a relational database management system that can be used as a data warehouse (DWH) when configured with features like columnstore indexes and data integration tools. However, it is primarily designed for transactional processing, and dedicated data warehouse solutions like Azure Synapse or Snowflake are optimized for large-scale analytical workloads. Cloud data warehouse roles often require knowledge of such specialized platforms and SQL skills.

What is the difference between ETL and DWH?

A Cloud Data Warehouse (DWH) is a centralized repository for storing large volumes of integrated data from multiple sources. ETL (Extract, Transform, Load) is the process used to extract data from source systems, transform it into a suitable format, and load it into the data warehouse. While ETL is a method for data integration, DWH is the storage environment that enables analytics and reporting.

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

AspectCloud Data WarehouseData Engineer
Primary RoleDesigning, implementing, and managing cloud-based data storage solutionsBuilding, maintaining, and optimizing data pipelines and infrastructure
Required SkillsSQL, cloud platforms (AWS, GCP, Azure), data modelingSQL, programming (Python, Java), ETL tools, cloud services
Work EnvironmentCloud platforms, data storage systemsData pipelines, cloud infrastructure, coding environments
CertificationsCloud certifications (AWS, GCP, Azure)Data engineering certifications (Google Cloud Professional Data Engineer, AWS Data Analytics)

While both roles involve working with data in cloud environments, a Cloud Data Warehouse focuses on managing and optimizing cloud storage solutions, whereas a Data Engineer builds and maintains the data pipelines and infrastructure that enable data analysis and reporting. They often collaborate but have distinct responsibilities within data ecosystems.

What are the key skills and qualifications needed to thrive as a Cloud Data Warehouse Engineer, and why are they important?

To thrive as a Cloud Data Warehouse Engineer, you need expertise in data modeling, SQL, cloud platforms (such as AWS, Azure, or Google Cloud), and ETL processes, typically supported by a degree in computer science or a related field. Familiarity with tools like Snowflake, Redshift, BigQuery, data integration platforms, and relevant certifications (e.g., AWS Certified Data Analytics) is often required. Strong problem-solving skills, attention to detail, and effective communication are important soft skills for collaborating with stakeholders and managing complex data solutions. These skills ensure the efficient design, implementation, and maintenance of scalable cloud data warehouses that support business intelligence and decision-making.

What is a cloud data warehouse?

A cloud data warehouse is a scalable storage and processing system hosted on cloud platforms that allows organizations to store, analyze, and manage large volumes of data. Data analysts and data engineers often use tools like SQL and cloud services such as Amazon Redshift, Google BigQuery, or Snowflake to perform data integration and querying tasks efficiently.

What is L1 L2 L3 data warehouse?

In the context of a cloud data warehouse, L1, L2, and L3 typically refer to different levels of data processing or storage layers. L1 often represents raw or foundational data, L2 involves transformed or cleaned data, and L3 includes aggregated or analyzed data for reporting. Understanding these levels helps data engineers and analysts manage data workflows effectively within cloud environments.

What are some common challenges faced by professionals working in Cloud Data Warehouse roles, and how can they be addressed?

Professionals in Cloud Data Warehouse roles often encounter challenges such as integrating data from diverse sources, ensuring data security and compliance, and optimizing query performance as data volumes scale. Addressing these challenges typically involves collaborating with data engineering, security, and DevOps teams to design robust data pipelines, implement access controls, and monitor system performance. Staying current with evolving cloud technologies and best practices is essential for maintaining efficiency and reliability in these environments.
More about Cloud Data Warehouse jobs
What job categories do people searching Cloud Data Warehouse jobs look for? The top searched job categories for Cloud Data Warehouse jobs are:
Cloud Data Warehouse jobs near you
Infographic showing various Cloud Data Warehouse job openings in the United States as of June 2026, with employment types broken down into 4% As Needed, 78% Full Time, 11% Part Time, 1% Temporary, 4% Contract, and 2% Nights. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $128,365 per year, or $61.7 per hour.

Data Warehouse & Analytics Specialist

Challenger School Human Resources

Sandy, UT • On-site

$80K - $95K/yr

Temporary

Medical, Dental, Vision, Retirement, PTO

Posted 5 days ago

Job description

Data Warehouse & Analytics Specialist
Location: Sandy, Utah (100% On-Site)
Department: Research, Operations, and R&D
About Challenger School
Challenger School is an independent private school organization committed to providing exceptional education and fostering critical thinking, personal responsibility, and intellectual growth. Our Research & Development team supports data-driven decision making across the organization and is actively building modern analytics, data warehouse, semantic modeling, and AI-enabled capabilities.
Position Overview
Challenger School is seeking a Data Warehouse & Analytics Specialist to help build trustworthy, well-documented, AI-ready data assets that support reporting, analytics, research, and operational decision making.
This role combines SQL/PYTHON analysis, data warehousing, semantic modeling, business intelligence, data governance, reporting validation, and AI-enabled analytics. The position serves as a bridge between technical systems and business users by translating database structures, reports, and metrics into clear, consistent business definitions.
The ideal candidate enjoys working deeply with SQL/PYTHON, understanding how business metrics are calculated, documenting data definitions, resolving inconsistencies, validating reports, and helping create reliable data structures that can be used by analysts, business users, and AI systems.
This position is heavily focused on SQL/PYTHON, documentation, data quality, warehouse analysis, semantic consistency, and business understanding rather than dashboard design or software engineering.
Responsibilities
  • Analyze SQL/PYTHON queries, views, reports, source systems, and warehouse structures to understand how business metrics are calculated.
  • Trace data lineage from operational systems through data warehouse transformations, reporting layers, and semantic models.
  • Translate technical data logic into clear business definitions.
  • Develop and maintain business glossaries, data dictionaries, metric definitions, and metadata documentation.
  • Validate report outputs against source systems and warehouse data.
  • Support the development and maintenance of Snowflake semantic models.
  • Create and maintain mappings between business terminology and physical database structures.
  • Review and validate AI-generated SQL/PYTHON, analytics, and business insights.
  • Work with stakeholders to standardize business definitions and reporting logic.
  • Support data quality, reconciliation, governance, and AI-readiness initiatives.
  • Help prepare trusted data assets for natural-language querying, AI-assisted reporting, and future analytics initiatives.

Required Qualifications
  • Strong SQL/PYTHON skills.
  • Experience working with relational databases, data warehouses, or cloud data platforms.
  • Ability to understand complex query logic and data transformations.
  • Strong analytical and problem-solving abilities.
  • Excellent written communication and documentation skills.
  • Strong attention to detail.
  • Ability to work effectively with technical and nontechnical stakeholders.

Preferred Qualifications
  • Experience with Snowflake or similar cloud data warehouse platforms.
  • Business intelligence or reporting experience.
  • Experience documenting business rules, metrics, or data definitions.
  • Familiarity with semantic models, governed metrics, or metadata management.
  • Experience with Python for data analysis or validation.
  • Familiarity with AI-assisted analytics tools and workflows.

Ideal Candidate
The ideal candidate enjoys solving data puzzles, untangling complex business logic, identifying why reports disagree, and transforming technical information into clear business definitions. They are patient, precise, intellectually curious, and committed to data quality, consistency, and accuracy.
Benefits
  • Medical, dental, and vision insurance
  • 401(k)
  • Paid time off
  • Professional development opportunities
  • Long-term career growth in analytics, data warehousing, semantic modeling, data governance, and AI-enabled data systems

If you enjoy detailed analytical work and want to help build the foundation for data-driven decision making across a growing educational organization, we encourage you to apply.
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