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Remote Data Engineer 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 ...

Virtuous Software

Lead Data Platform Engineer

Phoenix, AZ · On-site +1

$113K - $136K/yr

We're hiring a Lead Data Platform Engineer to design, build, and own the systems that power our data ecosystem. This role is ideal for a highly motivated self-starter who is comfortable with ...

Virtuous Software

Data Migration Engineer

Phoenix, AZ · On-site +1

$113K - $136K/yr

While this role is open to remote candidates within the US, we're initially prioritizing candidates ... Position Summary A Virtuous Data Migration Engineer will be in charge of extracting, mapping ...

Hospice of the Valley

Senior Data & AI Engineer

Phoenix, AZ · Remote

$100K - $136K/yr

Position Profile The Senior Data & AI Engineer will need to have deep handsa'on experience in Snowflake, Microsoft Fabric (incl. OneLake), and healthcare data ecosystems. The ideal candidate ...

Owens & Minor

Senior Manager, Data Engineering

Phoenix, AZ · On-site +1

$140K - $155K/yr

The role is fully remote. Applicants in different states are encouraged to apply. Key Responsibilities Leadership & Team Management - Lead, mentor, and develop a team of data engineers and BI ...

Insight

You will have the flexibility to work fully remote from anywhere across Arizona. Insight at a ... At least 5 years specifically focused on Data Engineering, Analytics, or Machine Learning. * Cloud ...

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All JobsRemote Data Engineer JobsRemote Data Engineer Jobs in Arizona

Remote Data Engineer information

See Arizona salary details

$41.5K

$120.9K

$165.4K

How much do remote data engineer jobs pay per year?

As of Jul 5, 2026, the average yearly pay for remote data engineer 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.

What Does a Remote Data Engineer Do?

As a remote data engineer, you focus on collecting, storing, and organizing large amounts of information. You work from home to design, develop, and maintain systems for the mining, warehousing, and processing of data. A data engineer communicates with employers, clients, or other data professionals to assess the needs of the project and develop and implement solutions to meet those needs. Data engineers also take steps to manage current database architecture and make updates when needed. Remote engineers typically handle their responsibilities in a cloud-based environment using “big data” tools, such as Amazon Web Services (AWS) and SQL.

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

AspectRemote Data EngineerRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related; SQL, Python, cloud certificationsBachelor's in Statistics, Data Science, or related; SQL, Excel, visualization tools
Work EnvironmentCollaborates with data engineering teams, cloud platforms, big data toolsWorks with business teams, dashboards, reporting tools
Industry UsageTech, finance, healthcare, e-commerceMarketing, finance, retail, healthcare
Common Search IntentBuilding data pipelines, data infrastructureData reporting, insights, visualization

Remote Data Engineers focus on designing and maintaining data pipelines and infrastructure, often requiring programming and cloud skills. Remote Data Analysts interpret data, create reports, and provide insights using visualization tools. While both roles work with data, their responsibilities and skill sets differ, making each suited for different career paths within data teams.

How do remote Data Engineers typically collaborate with other team members across different time zones?

Remote Data Engineers often work with cross-functional teams, including data scientists, analysts, and software engineers, many of whom may be located in different parts of the world. Collaboration is usually facilitated through project management tools, version control platforms, and regular virtual meetings. It’s common to have a mix of synchronous check-ins and asynchronous communication, allowing for flexible scheduling and efficient handoffs. Strong written communication skills and proactive status updates are essential for staying aligned with team objectives and project deadlines.

What is a Remote Data Engineer?

A Remote Data Engineer is a professional who designs, builds, and maintains data pipelines, databases, and data processing systems while working from a location outside of a traditional office. They collaborate with data scientists, analysts, and other stakeholders to ensure data is collected, stored, and made accessible efficiently and securely. Remote Data Engineers use programming languages like Python or Scala, work with technologies such as SQL, Hadoop, or cloud platforms, and address challenges related to data quality and scalability. Their remote role allows them to work for companies regardless of geographic location, often relying on virtual collaboration tools to stay connected with their teams.

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 in languages like Python or Scala, expertise in SQL, data modeling, and a background in computer science or a related field. Familiarity with cloud platforms (such as AWS, Azure, or GCP), big data tools (like Hadoop and Spark), and certifications in cloud or data engineering are highly valued. Excellent problem-solving, communication, and self-management skills help remote data engineers collaborate effectively and stay productive in a distributed environment. These competencies ensure reliable data pipelines, scalable solutions, and seamless teamwork, which are critical for organizational success in data-driven projects.
More about Remote Data Engineer jobs
What are the most commonly searched types of Data Engineer jobs in Arizona? The most popular types of Data Engineer jobs in Arizona are:
What are popular job titles related to Remote Data Engineer jobs in Arizona? For Remote Data Engineer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Remote Data Engineer jobs in Arizona look for? The top searched job categories for Remote Data Engineer jobs in Arizona are:
What cities in Arizona are hiring for Remote Data Engineer jobs? Cities in Arizona with the most Remote Data Engineer job openings:
Remote Data Engineer jobs near you
Senior Data & AI Engineer

Senior Data & AI Engineer

Phoenix Staff

Phoenix, AZ • On-site, Remote

$50 - $60/hr

Contractor

Posted 4 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.