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Data Engineers Jobs in Arizona (NOW HIRING)

Perficientcorp Inc

GCP Data Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

All Visas Accepted ⚡ Quick Client Feedback | Interview Guaranteed for Qualified Candidates We are actively seeking experienced GCP Data Engineers for a long-term contract opportunity with a leading ...

Smart Synergies

Data Engineering Lead

Glendale, AZ · On-site

Lead and mentor a team of data engineers, providing technical guidance and fostering professional development. Collaborate with cross-functional teams, including data scientists, business analysts ...

Strategic Staffing Solutions

Lead Data engineer

Chandler, AZ · On-site

$116K - $140K/yr

Ability to work with Data Engineers in discovering and optimizing bottlenecks in the AI/ML pipeline for real-time or near-real-time applications that consumes large throughput of data * Perform ...

Perficientcorp Inc

Python Data Engineer

Phoenix, AZ · On-site

... Data Engineers / API Developers for enterprise-level projects. If you have strong expertise in PySpark, GCP, and scalable API development, we'd love to connect with you. Required Skills: PySpark ...

Tata Consultancy Services

SRE with Data Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

... engineers, analysts, and business stakeholders, to gather and define data requirements. • Implement data security, governance, and compliance measures in big data environments. • Diagnose and ...

Deloitte

Sr Databricks Data Engineer

Tempe, AZ

$109K - $131K/yr

Lead, coach, and develop teams of data engineers and architects, fostering technical growth and effective project delivery. Data Governance: Consult on, design, and implement governance, security ...

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All JobsData Engineers JobsData Engineers Jobs in Arizona

Data Engineers information

See Arizona salary details

$41.5K

$120.9K

$165.4K

How much do data engineers jobs pay per year?

As of Jul 26, 2026, the average yearly pay for data engineers 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.

Is a data engineer a high paying job?

Data engineers typically earn high salaries due to their specialized skills in designing and maintaining data pipelines, working with tools like SQL, Python, and cloud platforms. Compensation varies by experience, location, and industry, but overall, it is considered a well-paying role in the tech field.

Is AI replacing data engineers?

AI is transforming the role of data engineers by automating routine tasks such as data cleaning and integration, but it does not replace the need for skilled professionals to design, build, and maintain data infrastructure. Data engineers are essential for managing complex data pipelines, ensuring data quality, and implementing scalable solutions using tools like SQL, Python, and cloud platforms. Their expertise remains critical in developing and overseeing AI systems and analytics workflows.

What does a data engineer actually do?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making.

What engineers make 500,000?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn salaries of $500,000 or more, especially in high-cost 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 do Data Engineers typically collaborate with Data Scientists and other team members on data-driven projects?

Data Engineers play a crucial role in enabling data-driven projects by designing, building, and maintaining the data infrastructure that Data Scientists and analysts rely on. They often work closely with Data Scientists to understand their data requirements, ensure data quality, and optimize data pipelines for efficient analysis. Collaboration involves frequent communication to align on data formats, data availability, and performance needs, as well as troubleshooting issues that may arise with data ingestion or transformation. This teamwork ensures that data is accessible, reliable, and actionable, which is essential for successful analytical and machine learning initiatives.

What is the difference between Data Engineers vs Data Analysts?

AspectData EngineersData Analysts
Required CredentialsBachelor's in Computer Science, Engineering, or related field; often certifications in cloud platforms or data engineering toolsBachelor's in Statistics, Mathematics, or related field; certifications in data analysis or visualization tools
Work EnvironmentBuild and maintain data pipelines, work with big data technologies, often in cloud environmentsAnalyze data, create reports and dashboards, work with business teams
Employer & Industry UsageTech companies, finance, healthcare, e-commerce; focus on data infrastructureMarketing, finance, retail, healthcare; focus on data insights for decision-making

Data Engineers focus on developing and maintaining data infrastructure, while Data Analysts interpret data to provide actionable insights. Both roles are essential but serve different functions within data teams.

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

To thrive as a Data Engineer, you need strong skills in programming (especially Python, Java, or Scala), database management, data modeling, and typically a degree in computer science or a related field. Familiarity with big data tools like Hadoop, Spark, SQL/NoSQL databases, and cloud platforms (AWS, Azure, or GCP) as well as relevant certifications are common technical requirements. Excellent problem-solving, attention to detail, and effective communication are soft skills that help Data Engineers excel in collaborative and fast-paced environments. These skills are crucial for ensuring robust, scalable, and efficient data pipelines that support reliable analytics and business decision-making.

What are Data Engineers?

Data Engineers are professionals who design, build, and maintain systems that collect, store, and process large amounts of data. Their primary role is to ensure that data is accessible, reliable, and efficiently structured for analysis by data scientists and other stakeholders. They work with various tools and technologies to create pipelines that move and transform data from multiple sources, making it usable for business intelligence and analytics. Data Engineers also focus on optimizing data workflows to ensure scalability and performance.
What are popular job titles related to Data Engineers jobs in Arizona? For Data Engineers jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Data Engineers jobs in Arizona look for? The top searched job categories for Data Engineers jobs in Arizona are:
What cities in Arizona are hiring for Data Engineers jobs? Cities in Arizona with the most Data Engineers job openings:
Data Engineers jobs near you
Infographic showing various Data Engineers job openings in Arizona as of July 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $120,881 per year, or $58.1 per hour.

GCP Data Engineer

Perficientcorp Inc

Phoenix, AZ • On-site

$113K - $136K/yr

Contractor

Posted 8 days ago

Job description

| GCP Data Engineer | Phoenix, AZ | Contract Opportunity
Location: Phoenix, AZ (Onsite/Hybrid)
Duration: 12+ Months
Experience Required: 5–7+ Years
Visa: All Visas Accepted 
⚡ Quick Client Feedback | Interview Guaranteed for Qualified Candidates
We are actively seeking experienced GCP Data Engineers for a long-term contract opportunity with a leading client.
Required Skills:
✅ Google Cloud Platform (GCP)
GCS
DataProc
BigQuery
Composer / Airflow
✅ Strong experience with:
PySpark & Spark
Python
Hadoop Ecosystem
SQL
Data Engineering & ETL Development
DataFrame-based Processing
Large-Scale Data Processing
Enterprise Big Data Platforms
Agile Methodologies
Nice-to-Have Skills:
➕ Spanner DB
➕ Graph Databases
➕ Scala
➕ Hive
➕ Pig
➕ MapReduce
⭐ Mandatory Requirement:
✔ Ex-American Express (Amex) Candidates Only
✔ Must provide complete Amex project/client details
We are accepting submissions only from candidates with prior American Express experience.