ZipRecruiter

Log In

2

Remote Data Engineering Jobs in Gilbert, AZ (NOW HIRING)

Mondo

Data Scientist

Phoenix, AZ · Remote

$65 - $75/hr

Remote (Candidate must reside in Pacific, Mountain, or Central time zone. Eastern time zone and ... Candidates whose current or most recent role carries a different title (Data Analyst, ML Engineer ...

Inherent Technologies

Azure Databricks Architect

Chandler, AZ · Remote

$65 - $84.75/hr

Minneapolis/Remote 12+ years of Data Solutions Design/Development Experience with at-least 2+ years ... engineering solutions with hands-on in any 2 or more of : Azure Data Factory, Azure DataBricks ...

Koantek

Databricks Platform Architect

Chandler, AZ · Remote

Lead Data Platform Architect / Data bricks Migration Lead Location: Remote Position Type: Contract ... Pipeline Engineering: Design distributed processing frameworks, control flows, and configuration ...

Koantek

Resource Manager

Chandler, AZ · Remote

Remote (Coverage for EST & PST required) Role Overview As the Resource Manager for Koantek ... Familiarity with the Databricks ecosystem or similar data engineering platforms.

previous page

Showing results 41-60

All JobsData Engineering JobsRemote Data Engineering JobsRemote Data Engineering Jobs in Gilbert, AZ

Remote Data Engineering information

See Gilbert, AZ salary details

$44.4K

$129.3K

$176.9K

How much do remote data engineering jobs pay per year?

As of Aug 18, 2026, the average yearly pay for remote data engineering in Gilbert, AZ is $129,302.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,100.00 and $137,100.00 per year, depending on experience, location, and employer.

What is remote data engineering?

Remote data engineering involves designing, building, and maintaining data systems and pipelines while working from a location outside of a traditional office. Remote data engineers use tools to collect, process, and store large sets of data, making it accessible for analysis and business decision-making. They collaborate with teams virtually, often using cloud-based technologies, to ensure that data infrastructure is reliable, scalable, and secure. This role requires strong technical skills in programming, databases, and data architecture, as well as the ability to communicate effectively in a distributed work environment.

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

To thrive as a Remote Data Engineer, you need strong programming skills (such as Python, Java, or Scala), experience with data modeling, ETL processes, and a solid understanding of database systems, often supported by a degree in computer science or a related field. Proficiency with big data tools like Apache Spark, Hadoop, cloud platforms (AWS, Azure, GCP), and certifications in these technologies is highly valued. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These competencies ensure effective data pipeline development, reliable data management, and seamless teamwork across distributed environments.

How do remote data engineers typically collaborate with other team members across different time zones?

Remote data engineers often work with distributed teams, which requires strong communication and organization skills. They collaborate using tools like Slack, Zoom, and project management platforms to stay aligned on data pipeline development, troubleshooting, and deployment. Regular stand-ups, asynchronous documentation, and clear communication of progress are essential for ensuring everyone is on the same page, regardless of location. Flexibility in working hours and proactive scheduling of meetings help facilitate effective collaboration and project delivery.

What is the difference between Remote Data Engineering vs Remote Data Analyst?

AspectRemote Data EngineeringRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; experience with SQL, Python, cloud platformsBachelor's in Statistics, Data Science, or related; proficiency in Excel, SQL, visualization tools
Work EnvironmentBuilds data pipelines, manages databases, works with cloud infrastructureAnalyzes data sets, creates reports, visualizes data insights
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, finance, retail, consulting

Remote Data Engineering focuses on designing and maintaining data infrastructure, while Remote Data Analysts interpret data to provide insights. Both roles require strong analytical skills but differ in technical depth and responsibilities.

What are the most commonly searched types of Data Engineering jobs in Gilbert, AZ?

The most popular types of Data Engineering jobs in Gilbert, AZ are:

What are popular job titles related to Remote Data Engineering jobs in Gilbert, AZ?

For Remote Data Engineering jobs in Gilbert, AZ, the most frequently searched job titles are:

What job categories do people searching Remote Data Engineering jobs in Gilbert, AZ look for?

The top searched job categories for Remote Data Engineering jobs in Gilbert, AZ are:

What cities near Gilbert, AZ are hiring for Remote Data Engineering jobs?

Cities near Gilbert, AZ with the most Remote Data Engineering job openings:

Remote Data Engineering jobs near you
Infographic showing various Remote Data Engineering job openings in Gilbert, AZ as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $129,302 per year, or $62.2 per hour.

Data Scientist

Mondo

Phoenix, AZ • Remote

$65 - $75/hr

Contractor

Medical, Dental, Vision, Retirement

Re-posted 3 days ago

Job description

Apply now: Senior Data Scientist , Remote. Start date is ASAP for this 12 Month Contract position.

Job Title: Senior Data ScientistLocation/Type: Remote (Candidate must reside in Pacific, Mountain, or Central time zone. Eastern time zone and international candidates will not be considered.)Start Date: ASAPDuration: Contract, 6  Months (extension likely)Compensation Range: $65/hr to $75/hrBenefits: Eligible for Health, Dental, Vision, and 401KVisa Sponsorship: Not eligible for visa sponsorship

Job Description:The client is seeking a Data Scientist with deep expertise in Generative AI, agentic architectures, and MLOps to design, build, and scale end to end AI solutions while embedding Responsible AI practices across the full development lifecycle. This role requires hands on MLOps maturity, not just model building, the candidate will own how models move from experimentation into production and stay reliable once they get there.

Job Summary:

  • Design and deploy end to end RAG solutions and autonomous AI agents in cloud and enterprise environments
  • Build and scale machine learning and AI models on cloud platforms, primarily AWS or Azure
  • Develop and maintain MLOps pipelines to support model deployment, monitoring, versioning, and governance
  • Own CI/CD for ML workflows, including automated retraining, model registry management, and rollback procedures
  • Implement model monitoring for drift, performance degradation, and data quality issues in production
  • Apply statistical modeling techniques to solve complex business problems
  • Collaborate with stakeholders across the organization to translate requirements into scalable AI solutions
  • Embed Responsible AI practices across model development, deployment, and governance workflows
  • Contribute across the full development lifecycle, from experimentation through production release

Requirements:

Must Haves:

  • Location: candidate must be based in Pacific, Mountain, or Central time zone. This is a hard requirement, not a preference.
  • Minimum 4 years of experience working specifically as a Data Scientist (title and scope must match, not adjacent titles like Data Analyst or ML Engineer alone)
  • Must currently or most recently hold a Data Scientist title (Data Scientist, Senior Data Scientist, Staff Data Scientist, Principal Data Scientist, etc.). Candidates whose current or most recent role carries a different title (Data Analyst, ML Engineer, Analytics Engineer, etc.)
  • Minimum 3 years of hands on MLOps experience, specifically model deployment, monitoring, and lifecycle management in production environments (not just model development or notebooks)
  • Direct experience with at least one MLOps tooling stack such as MLflow, Kubeflow, SageMaker Pipelines, or Azure ML Pipelines
  • Master's degree in a STEM field
  • 4 years of proficiency in SQL
  • 4 years of proficiency in Python
  • Hands on experience with AWS or Azure cloud platforms
  • Proficiency with Git for version control
  • Strong communication skills with demonstrated ability to work cross functionally with stakeholders

Nice to Haves:

  • Experience with Snowflake for data warehousing and analytics
  • Hands on experience with AWS specifically, in addition to general cloud proficiency
  • Startup or fast paced environment mindset with comfort navigating ambiguity
  • Active personal use of AI tools and familiarity with the evolving AI landscape