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Cloud Data Engineer Jobs (NOW HIRING)

Hewlett Packard Enterprise

Cloud Data Engineer

Aguadilla, PR · Hybrid

$102K - $122K/yr

Cloud Data Engineer This role has been designed as 'Hybrid' with an expectation that you will work on average 2 days per week from an HPE office. Who We Are: Hewlett Packard Enterprise is the global ...

Hewlett Packard Enterprise

Cloud Data Engineer

San Juan, PR · Hybrid

$112K - $134K/yr

Cloud Data Engineer This role has been designed as 'Hybrid' with an expectation that you will work on average 2 days per week from an HPE office. Who We Are: Hewlett Packard Enterprise is the global ...

Hewlett Packard Enterprise

Cloud Data Engineer

San Jose, CA

$134K - $161K/yr

Cloud Data Engineer This role has been designed as ''Onsite' with an expectation that you will primarily work from an HPE office. Who We Are: Hewlett Packard Enterprise is the global edge-to-cloud ...

HKA Enterprises

Cloud Data Engineer : 197273

Columbus, OH · On-site

$42.04/hr

Senior Cloud Data Engineer (Contract | W2 Only | 1-Year with possible extension) Location: Columbus, Ohio Employment Type: W2 Contract (1 Year) Work Authorization: Must be authorized to work in the ...

ARC Group

Azure Cloud Data Engineer

Weston, FL · Remote

$108K - $130K/yr

AZURE DATA ENGINEER (REMOTE) ARC Group has an immediate opportunity for an aspiring Azure / Cloud Data Engineer to join our global client's growing team of data experts. This is 100 REMOTE and a ...

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How much do cloud data engineer jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for cloud data engineer in the United States is $62.89, according to ZipRecruiter salary data. Most workers in this role earn between $53.61 and $71.63 per hour, depending on experience, location, and employer.

What are some common challenges a Cloud Data Engineer faces when migrating data to the cloud?

Cloud Data Engineers often encounter challenges such as ensuring data security and compliance during migration, optimizing data pipelines for cloud performance, and managing data integrity across distributed systems. They must work closely with cross-functional teams to minimize downtime and avoid data loss, and frequently address issues related to data format compatibility and legacy system integration. Staying up-to-date with evolving cloud technologies and best practices is also essential for successful data migration projects.

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

AspectCloud Data EngineerData Analyst
Required CredentialsCloud certifications (e.g., AWS, Azure), SQL, programming skillsData analysis certifications, SQL, Excel, visualization tools
Work EnvironmentCloud platforms, big data tools, data pipelinesData visualization, reporting, business insights
Employer & Industry UsageTech companies, finance, healthcare, cloud service providersMarketing, finance, retail, business intelligence

While Cloud Data Engineers focus on building and maintaining cloud-based data infrastructure, Data Analysts interpret data to provide business insights. Both roles require SQL skills, but Cloud Data Engineers emphasize cloud platforms and data pipeline development, whereas Data Analysts focus on data visualization and reporting.

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

To excel as a Cloud Data Engineer, you need strong expertise in data modeling, ETL processes, programming languages like Python or SQL, and a solid understanding of cloud platforms such as AWS, Azure, or Google Cloud, often supported by a relevant degree and cloud certifications. Familiarity with tools like Apache Spark, Hadoop, cloud storage systems, and data pipeline orchestration frameworks is typically required. Strong problem-solving skills, attention to detail, and effective communication help you deliver scalable solutions and collaborate with cross-functional teams. These competencies are essential for building robust, secure, and efficient data infrastructure that supports business intelligence and analytics.

What is a Cloud Data Engineer?

A Cloud Data Engineer is an IT professional who designs, builds, and manages scalable data infrastructure and pipelines in cloud environments. They work with cloud platforms like AWS, Google Cloud, or Azure to create systems that collect, process, store, and analyze large volumes of data. Their responsibilities include setting up data lakes and warehouses, ensuring data quality and security, and enabling data-driven applications. Cloud Data Engineers collaborate with data scientists, analysts, and other stakeholders to support business intelligence and analytics initiatives.
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Cloud Data Engineer jobs near you
Infographic showing various Cloud Data Engineer job openings in the United States as of May 2026, with employment types broken down into 68% Full Time, 30% Part Time, 1% Contract, and 1% Nights. Highlights an 79% Physical, 6% Hybrid, and 15% Remote job distribution, with an average salary of $130,802 per year, or $62.9 per hour.

Databricks Data Engineer (Cloud Data Engineering)

Prophecy Technologies

Remote

$117K - $140K/yr

Full-time

Posted 3 days ago

Job description

Job Summary
We are seeking an experienced Databricks Data Engineer to support cloud-based data engineering initiatives focused on batch processing, lakehouse architecture, and large-scale data migration. This role will be part of the Cloud Data Engineering team, responsible for designing, building, and optimizing data pipelines using Databricks and Azure cloud technologies. The ideal candidate will bring a data-first mindset and strong problem-solving skills to deliver scalable and high-quality data solutions.
Experience
  • 8-12 years of overall experience
  • 10+ years of experience in data engineering and architecture preferred

Key Responsibilities
  • Design, build, and optimize high-throughput batch data pipelines using Databricks
  • Develop and maintain Databricks-based data lake and lakehouse architectures on Azure or AWS
  • Migrate existing data platform solutions to cloud-based environments
  • Engineer scalable and performant data solutions using Azure Cloud PaaS technologies
  • Analyze requirements, evaluate technology effectiveness, and recommend data engineering improvements
  • Debug and troubleshoot complex, multi-threaded data processing applications
  • Collaborate with cross-functional IT and business teams to deliver reliable data solutions
  • Act as a subject matter expert on complex cloud data engineering initiatives
  • Ensure data quality, performance optimization, and best engineering practices

Required Skills & Experience
  • Strong experience with Databricks batch processing and data lake design
  • 3+ years of hands-on experience designing and optimizing Databricks data pipelines
  • 3+ years of experience working with Databricks Lakehouse architectures on Azure or AWS
  • Hands-on experience with Microsoft Azure technologies including:
  • Azure Databricks
  • Azure Data Factory
  • Event Hub
  • Synapse Analytics
  • Delta Lake
  • Cosmos DB
  • Experience with Scala and cloud DevOps practices
  • Proficiency with Git and Jenkins for build automation and configuration management
  • Strong troubleshooting, analytical, and problem-solving skills
  • Excellent written and verbal communication skills

Competencies
  • Cloud Data Engineering
  • Databricks Architecture & Optimization
  • Data Architecture and Modeling
  • Collaboration and Independent Execution

Preferred Skills
  • Experience with Big Data ecosystems and NoSQL databases
  • Experience with Azure, AWS, or other public cloud platforms
  • Prior experience leading or supporting large-scale data engineering projects
  • Knowledge of Agile development methodologies

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