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Remote Data Engineering Jobs in Arizona (NOW HIRING)

Phoenix Staff

Senior Data & AI Engineer

Phoenix, AZ · On-site +1

$50 - $60/hr

Phoenix, AZ (hybrid remote) Type: 6-month contract to hire Pay: $50-60/hr We're looking for a Senior Data & AI Engineer to lead the design and delivery of secure, scalable data and AI solutions ...

Carrington

Senior, Data Engineer

Chandler, AZ · Remote

$140K - $160K/yr

Come join our amazing team and work remote from home! What you'll do: Under direct supervision ... data engineering, such as Python or Java Our Company: Carrington Mortgage Holdings is a holding ...

Judge Group, Inc.

BI Data Analyst

Scottsdale, AZ · On-site

$35 - $45/hr

Scottsdale, AZ Remote: NO Rate: 35$-45$/hr Length of Assignment: 6 months +, Contract to Hire The ... Ensure dashboards adhere to formatting and security standards Data Engineering & SQL: Designs ...

Mondo

Product Owner

Phoenix, AZ · Remote

$55 - $60/hr

Remote (PST hours) Start Date Is: ASAP Duration: 12-month contract (potential to convert ... Act as Product Owner within Agile/Scrum teams supporting data engineering and BI initiatives

Independence Pet Group

Senior Data Engineer

Scottsdale, AZ · Remote

$106K - $145K/yr

POSITION LOCATION: 100% remote reporting to: 11333 N Scottsdale Rd., Suite 160, Scottsdale, AZ ... Engineering, Business Analytics, Management Information Systems or related field of study and 3 ...

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Showing results 1-20

All JobsRemote Data Engineering JobsRemote Data Engineering Jobs in Arizona

Remote Data Engineering information

See Arizona salary details

$41.5K

$120.9K

$165.4K

How much do remote data engineering jobs pay per year?

As of Jun 23, 2026, the average yearly pay for remote data engineering in Arizona is $120,881.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,700.00 and $128,100.00 per year, depending on experience, location, and employer.

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 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, and why are they important?

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.

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 Arizona? The most popular types of Data Engineering jobs in Arizona are:
What are popular job titles related to Remote Data Engineering jobs in Arizona? For Remote Data Engineering jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Remote Data Engineering jobs in Arizona look for? The top searched job categories for Remote Data Engineering jobs in Arizona are:
What cities in Arizona are hiring for Remote Data Engineering jobs? Cities in Arizona with the most Remote Data Engineering job openings:
Remote Data Engineering jobs near you
Infographic showing various Remote Data Engineering job openings in Arizona as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $120,881 per year, or $58.1 per hour.
Senior Data & AI Engineer

Senior Data & AI Engineer

Phoenix Staff

Phoenix, AZ • On-site, Remote

$50 - $60/hr

Contractor

Posted 22 days ago

Job description

Title: Senior Data & AI Engineer

Location: Phoenix, AZ (hybrid remote)

Type: 6-month contract to hire

Pay: $50-60/hr

We’re looking for a Senior Data & AI Engineer to lead the design and delivery of secure, scalable data and AI solutions within complex healthcare environments. The position focuses on building modern data platforms, integrating diverse clinical and claims datasets, and operationalizing machine learning models that improve cost, quality, and patient outcomes.

Your role

·       Design, implement, and optimize data platforms using Snowflake and Microsoft Fabric, including Lakehouses, Warehouses, OneLake, and engineering pipelines.

·       Build and maintain scalable ingestion frameworks for batch and streaming data sources such as APIs, ADLS, SFTP, and event streams with full lineage and governance.

·       Develop secure data environments that comply with HIPAA and PHI requirements using role-based access, masking, tokenization, and de-identification.

·       Create conceptual, logical, and physical data models using dimensional, normalized, and data vault approaches.

·       Transform and normalize structured and unstructured healthcare data including claims, eligibility, enrollment, provider, and clinical documentation.

·       Integrate and harmonize data using FHIR, HL7, X12/EDI 837/835, NCPDP, and CMS standards across payer, provider, EHR, and HIE systems.

·       Build and deploy machine learning pipelines for risk modeling, utilization forecasting, fraud detection, quality measurement, and care gap analysis.

·       Operationalize models with strong MLOps practices including versioning, CI/CD, monitoring, and drift detection.

·       Implement data cataloging, metadata management, lineage tracking, and quality validation using tools such as Microsoft Purview or equivalent.

·       Monitor and optimize pipeline performance, cost, and reliability across Snowflake and Fabric environments.

·       Collaborate with clinicians, actuaries, product teams, and analysts to translate business needs into scalable technical solutions.

·       Document architecture, data mappings, and design standards while mentoring engineers and contributing to enterprise best practices.

What you’ve got

·       8+ years of experience in data engineering or analytics with at least 5 years of hands-on Snowflake expertise including virtual warehouses, tasks, streams, Snowpipe, RBAC, masking, and data sharing.

·       2+ years of experience with Microsoft Fabric including OneLake, Lakehouses, Warehouses, Dataflows Gen2, Notebooks, and Pipelines.

·       Advanced SQL skills with strong experience in ETL/ELT development using Python, dbt, Dataflows, or Fabric/ADF pipelines.

·       Deep knowledge of healthcare data standards including CMS datasets, FHIR, HL7, X12/EDI, provider data, eligibility, and claims processing.

·       Strong data modeling experience including dimensional modeling, SCD types, surrogate keys, 3NF, and data vault methodologies.

·       Experience building and deploying machine learning solutions using tools such as scikit-learn, PyTorch, TensorFlow, Azure ML, or Fabric ML.

·       Practical experience managing HIPAA compliance, PHI handling, auditing, and secure access controls within cloud data environments.

·       Experience working with both structured data formats such as Parquet and CSV and unstructured data such as clinical notes and PDFs.

·       Strong communication skills with the ability to produce mapping specifications, lineage documentation, and present technical trade-offs clearly.

·       Preferred: Experience with Epic or Cerner integrations, HEDIS or risk adjustment programs, MLOps tools such as MLflow or GitHub Actions, Power BI semantic modeling, and relevant Snowflake or Microsoft certifications.

To find more great tech-centric jobs, please visit www.phoenixstaff.com.