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Remote Data Engineer Jobs in Arizona (NOW HIRING)

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 ...

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 ...

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 ...

Judge Group, Inc.

BI Data Analyst

Scottsdale, AZ · Remote

$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 ...

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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 Jun 15, 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.

Can a data engineer work remotely?

Yes, data engineers can work remotely, especially as many companies adopt flexible work arrangements. Remote data engineering roles often require strong skills in cloud platforms, data pipelines, and collaboration tools, and may involve regular virtual communication with teams. The feasibility depends on the company's policies and the specific job requirements.

Will AI replace data engineer?

AI is unlikely to fully replace data engineers, as their role involves designing, building, and maintaining data pipelines and infrastructure that require human oversight and expertise. Instead, AI tools can augment their work by automating routine tasks, allowing data engineers to focus on complex problem-solving and system architecture. Skills in programming, cloud platforms, and data management remain essential for the role.

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.

What engineers make $500,000?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn $500,000 or more annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires specialized certifications, leadership roles, and a strong track record of managing complex data infrastructure.

How to make $1000 a week remote?

A remote data engineer can earn $1000 or more per week by working full-time for a company, freelancing on project-based platforms, or offering specialized skills such as data pipeline development, cloud computing, or machine learning. Building a strong portfolio, gaining relevant certifications, and mastering tools like SQL, Python, and cloud services can increase earning potential.
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
Lead Data Platform Engineer

Lead Data Platform Engineer

Virtuous Software

Phoenix, AZ • On-site, Remote

$113K - $136K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 2 days ago

Job description

About Us
Virtuous is on a mission to inspire global generosity by helping nonprofits build better relationships with their donors. We offer a modern software platform that provides mid-sized charities with elegant tools for fundraising, marketing, volunteerism, and online giving.
Our talented team is driven to disrupt the status quo in the nonprofit sector. We are hungry, humble, and committed to delivering best-in-class software solutions, customer success interactions, and sales experiences to the world's leading nonprofits
We also recognize the importance of giving back and making a difference in the communities where we live and work. That's why we practice radical generosity by volunteering at nonprofits or going the extra mile for our team and the customers we serve. We take our work seriously, but we don't take ourselves too seriously. We believe that life is too short not to love what you do.
The ideal candidate for Virtuous embodies our values by:
  • Asking questions with a spirit of curiosity
  • Giving feedback freely with candor & grace, welcoming it in return
  • Displaying a passion for philanthropy and technology
  • Serving with joy. Everyone is willing to make the coffee!
  • Celebrating the wins & milestones of others
  • Assuming good intent & demonstrating trust in others
  • Pursuing relationships with people different from themselves & creates space to be human

Find our core values & more here.
Position Summary
Virtuous is evolving its data platform into an AI-ready foundation that powers trusted decision-making and self-service analytics across the company.
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 ambiguity and thrives at the intersection of systems design, business semantics, and AI enablement.
This is not a traditional data engineering role focused on building one-off pipelines, dashboards, or ad hoc reports. Success in this role comes from designing and building durable platform capabilities - security models, access patterns, cost controls, and shared data foundations - that enable teams (and AI systems) to safely and confidently use data at scale.
You'll work closely with the Director of Data Operations as well as our Finance, Product, Engineering and Security Teams to ensure our data platform is accurate, governable, and ready to support AI-enabled workflows across the company.
What You'll Build & Own
Data Platform & AI-Enablement
  • Own the evolution of Virtuous's data platform, primarily on Snowflake and dbt, as a secure, scalable, and AI-ready system.
  • Design data models, metadata, and access patterns that support natural-language querying and AI-assisted analysis.
  • Partner with Data Operations and Teams across the company to ensure data structures are accurate, reusable, and aligned with business definitions.
  • Prepare data foundations that allow AI tools to deliver consistent, timely, and trustworthy answers.
  • Ensure AI systems access data exclusively through governed service accounts and role-scoped permissions, with query activity auditable and restricted according to enterprise data classification and access standards.
Access, Trust & Governance by Design
  • Architect and implement role-based access controls within Snowflake and related data systems (including row- and column-level security), ensuring enforcement aligns with enterprise IAM standards, approved access policies, and centralized identity governance processes.
  • In partnership with Security Operations and IT, translate approved enterprise access and compliance policies into enforceable platform-level controls, and maintain technical configurations to ensure ongoing alignment with those standards.
  • Ensure all platform-level access controls integrate with the enterprise identity provider (SSO, SCIM, role lifecycle management), and support automated provisioning, deprovisioning, and periodic access certification processes.
  • Build governance patterns that are enforced by design - not by manual process.
  • Support periodic access reviews and control validation processes in coordination with Security and Compliance teams, ensuring appropriate separation of duties between policy definition, approval, and technical implementation.
Platform Leverage & Standards
  • Build and maintain CI/CD pipelines, testing strategies, and deployment patterns for dbt and Snowflake.
  • Design deployment, testing, and validation patterns that make accuracy the default.
  • Establish platform standards, templates, and best practices that enable others to move faster without sacrificing quality or security.
  • Increase the amount of trusted work the organization can do without increasing Data Ops involvement.
  • Reduce ad hoc work by building reusable systems and guardrails.
  • Act as a technical leader and thought partner across data-related initiatives.
Reliability, Cost & Performance
  • Own Snowflake warehouse strategy, resource governance, and cost optimization.
  • Continuously improve performance, scalability, and reliability across the data platform.
  • Identify and eliminate inefficiencies that increase cost, risk, or operational overhead.
  • Collaborate with IT and Cloud Engineering to ensure Snowflake networking, storage integrations, and data movement patterns align with enterprise cloud security baselines, network segmentation standards, and infrastructure governance policies.

What Success Looks Like
  • Teams reliably self-serve data and insights without increasing DataOps workload or risk.
  • AI-powered tools consistently answer business questions accurately, using governed data, with access enforced by role and context.
  • Data access, governance, and correctness are enforced by platform design rather than manual review or process.
  • Platform improvements materially reduce cost, operational risk, or time-to-insight.
  • Shared, trusted models replace bespoke datasets and one-off definitions.
  • At least one company-critical initiative (e.g., AI enablement, cost optimization, access expansion) succeeds specifically because of systems you designed and built.

Who This Role is For
  • Care about leverage, durability, and outcomes - not just shipping artifacts.
  • Think deeply about how AI and automation change the role of data platforms.
  • Are highly self-directed and motivated, and take pride in ownership.
  • Thrive in ambiguity and are comfortable making decisions with incomplete information.
  • Are motivated by leverage, correctness, and long-term impact - not ticket volume or titles.
  • Readily navigate cross-functional tradeoffs to build shared data foundations that serve the whole company, not individual teams.

You Must Have
  • 7+ years of experience in data engineering, platform engineering, or related infrastructure roles, with ownership of production systems.
  • Deep expertise in Snowflake, especially:
    • Roles and RBAC
    • Row-level and column-level security
    • Warehouse design and cost optimization
    • Performance tuning and governance
  • Strong experience using dbt to build and maintain shared data models, including macro development, testing strategies, source freshness, group model security implementation, and production deployment patterns..
  • Advanced SQL skills and experience designing reliable ELT/ETL pipelines.
  • Proven systems-thinking mindset, with the ability to reason about tradeoffs across correctness, access, cost, and speed.
  • Clear communicator who can explain complex technical concepts to both technical and non-technical partners.

Nice to Have
  • dbt certification strongly preferred
  • Experience enabling AI/ML or natural-language data access.
  • Familiarity with data observability, lineage, or metadata tooling.
  • Experience designing platforms for self-service analytics.
  • Exposure to BI tools such as Sigma, Looker, or Tableau.
  • Experience working in lean, fast-growing organizations where leverage matters more than headcount.

What We Offer
  • Market competitive pay leveraging Carta data
  • Employee recognition through Bonusly (birthdays, anniversaries, achievements, etc.)
  • 401(k) retirement plan with company matching- 50% match up to 6% of compensation after 90 days
  • We value our employee's work-life balance and encourage taking advantage of Unlimited PTO
  • Supportive time off including paid volunteer days and company holidays
  • Employer-contributed healthcare benefits, encompassing medical, dental, and vision coverage, with plans available for dependents and choices for Health Savings Accounts (HSA) and Flexible Spending Accounts (FSA).
  • 12 weeks primary parent leave, 4 weeks secondary parent leave - full pay (adoption as well)
  • We pride ourselves on Community and host exciting company outings and events.

We've recently noticed an increase in recruitment scams where individuals are impersonating recruiters to obtain personal or financial information through fraudulent interviews and job offers.
Please note that all legitimate communication from Virtuous will only come from the @virtuous.org domain. If you receive a message from other domains, even if they look similar (e.g., virtuouscareers.org or virtuousjobs.com), they are not legitimate and we recommend disregarding it immediately.

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