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Data Engineer Project Jobs in Arizona (NOW HIRING)

Senior Data Engineer

Scottsdale, AZ ยท On-site

$106K - $144K/yr

We are seeking a Senior Data Engineer with the technical expertise, architectural insight, and ... Own projects end-to-end and deliver measurable results. * Diagnose and resolve complex data issues ...

Posted today

Big Data Engineer

Phoenix, AZ

$55.25 - $73.25/hr

... engineering and systems integration. Our tightly integrated offerings are tailored to each clients ... Implemented complex projects dealing with the considerable data size (GB/ PB) and with high ...

Mid-Senior Data Engineer

Phoenix, AZ ยท Hybrid

$100K - $115K/yr

Hybrid / Onsite as needed (project-dependent) Salary: $100,000 - $115,000 We are partnering with an organization seeking a skilled Data Engineer to support the design, build, and optimization of a ...

Senior Data Engineer

Phoenix, AZ ยท Hybrid

$100K - $135K/yr

The Senior Data Engineer is responsible for creating sustainable reporting, analytic, and data ... complex projects, considering capabilities, risks, and system dependencies. 2) Apply an ...

Senior Data Engineer

Phoenix, AZ ยท Hybrid

$100K - $135K/yr

The Senior Data Engineer is responsible for creating sustainable reporting, analytic, and data ... complex projects, considering capabilities, risks, and system dependencies. 2) Apply an ...

Data Engineer - Senior Associate

Phoenix, AZ ยท On-site

$77K - $202K/yr

... a Data Engineer - Senior Associate, you will focus on designing and building data infrastructure ... your projects. This position offers a chance to develop a deeper understanding of the business ...

Showing results 21-40

Data Engineer Project information

What is a data engineer project?

A Data Engineer Project refers to a specific initiative or assignment undertaken by data engineers to design, build, and maintain systems that gather, process, and store large volumes of data. These projects often involve creating data pipelines, integrating multiple data sources, ensuring data quality, and optimizing storage solutions for analytics or business intelligence. Such projects are critical for organizations to manage their data efficiently and enable data-driven decision-making. Data Engineer Projects can range from building a data warehouse to implementing real-time data streaming solutions.

What are some common challenges faced by data engineers working on project-based teams?

Data Engineers on project-based teams often encounter challenges such as integrating data from disparate sources, ensuring data quality and consistency, and meeting tight project deadlines. Collaboration with data scientists, analysts, and software engineers is crucial, requiring clear communication to translate business needs into robust data pipelines. Additionally, adapting to evolving technologies and toolsets is essential for the successful delivery of scalable and maintainable solutions.

What is the difference between Data Engineer Project vs Data Engineer?

AspectData Engineer ProjectData Engineer
CredentialsTypically requires a degree in Computer Science, Data Science, or related fields; certifications like AWS, Google Cloud, or Azure are commonSimilar credentials; often holds certifications in cloud platforms and data tools
Work EnvironmentProject-based, often temporary teams working on specific data solutionsFull-time role within organizations, maintaining ongoing data pipelines and infrastructure
Industry UsageUsed across industries for specific data initiativesCore role in data-driven companies and departments
Search & Comparison IntentOften searched for project-based roles or freelance opportunitiesMore common in job searches for permanent positions

In summary, Data Engineer Projects focus on temporary, goal-specific data tasks, while Data Engineers hold ongoing roles responsible for maintaining data infrastructure. Both roles require similar skills and certifications but differ mainly in scope and employment type.

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 proficiency in programming (Python, Java, or Scala), data modeling, and database management, often supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), ETL systems, cloud platforms (AWS, Azure, GCP), and relevant certifications is highly beneficial. Analytical thinking, problem-solving, and effective communication are crucial soft skills for collaborating with data teams and stakeholders. These competencies are essential for building reliable data pipelines and ensuring data availability and quality to drive business insights.
What cities in Arizona are hiring for Data Engineer Project jobs? Cities in Arizona with the most Data Engineer Project job openings:
Infographic showing various Data Engineer Project job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Senior Data Engineer

CNA National Warranty Corp

Scottsdale, AZ โ€ข On-site

$106K - $144K/yr

Full-time

Posted 16 hours ago

Posted today


Job description

We are seeking a Senior Data Engineer with the technical expertise, architectural insight, and problem-solving skills to design, build, and maintain our modern data platform. The ideal candidate will be a hands-on engineer who can deliver at scale, ensure data quality, and work across teams to support both operational and analytical workloads.

Responsibilities
  • Design, build, and maintain scalable data pipelines (ETL/ELT) for both batch and streaming use cases.
  • Implement data validation and integrity frameworks, ensuring accuracy, completeness, and reconciliation across systems.
  • Administer and optimize cloud-based data services (AWS, Snowflake, Databricks, etc.).
  • Ensure compliance with data governance and regulations (PCI-DSS, GDPR, CPRA, SOX, etc.).
  • Deliver proof of concepts and lightweight prototypes to validate architectural improvements.
  • Collaborate with business units, audit teams, and stakeholders to align data architecture with organizational needs.
  • Support reporting and analytics teams by enabling Tableau (or future-state tools) through well-structured data models and governance.
  • Seek out new work proactively and mentor other team members.
  • Own projects end-to-end and deliver measurable results.
  • Diagnose and resolve complex data issues quickly.
Qualifications
  • Bachelor’s degree in Computer Science, Information Technology, or equivalent experience.
  • 10+ years of experience in data engineering.
  • Mastery of complicated SQL for loading data, including complex joins, subqueries, windowing functions, and common table expressions.
  • Advanced proficiency in Python, developing and supporting robust pipelines, frameworks, and automation solutions.
  • Proven history designing and managing Data Warehousing solutions including proper loading techniques, star schema modeling, slowly changing dimensions, and aggregate strategies.
  • Strong understanding of OLTP modeling (3NF) and how to denormalize for performance or downstream use.
  • Production experience with unstructured and semi-structured data (e.g., JSON, MongoDB, APIs) and integrating it into enterprise data ecosystems.
  • Practical expertise implementing and optimizing pipeline orchestration with tools such as Airflow or Prefect.
  • Experience implementing and optimizing 3rd party transformation tools such as dbt, Talend, or FiveTran.
  • Demonstrated success in delivering scalable solutions using cloud-based data platforms like Snowflake or Databricks.
  • Applied experience leveraging AWS data services (S3, Glue, Redshift, Lambda, Secrets Manager, etc.) in secure and cost-effective ways.
  • Demonstrated ability to ensure compliance with regulatory requirements including PCI-DSS, GDPR, CPRA, CCPA, and SOX.
  • Effective communication skills for engaging both technical and non-technical audiences and collaborating with business and audit stakeholders.
  • Proven capability mentoring peers, promoting best practices, and contributing to team growth.
  • High adaptability to changing requirements, emerging technologies, and competing priorities.
  • Nice to have: Hands-on experience with Data Lake and Lakehouse technologies (e.g., Delta Lake, Iceberg, Hudi) for managing large-scale data assets.

This role is critical to our data engineering practice. We are looking for a hands-on leader who can operate in both structured and fast-changing environments while delivering high-quality, scalable solutions.

About CNA National

CNA National (CNAN) offers service contracts, warranties and other protection products to vehicle purchasers through franchised automobile dealerships nationwide. Founded in 1982 and headquartered in Scottsdale, Arizona, we set out to redefine the service contract industry with a commitment to being the best and doing the right thing. More than 40 years later, we remain true to that vision, evolving alongside the auto industry and delivering top-notch products with exceptional customer service.

Our organizational culture thrives on challenge and engagement, providing opportunities for employees to learn, grow, and feel a sense of purpose within our dynamic workplace.

In 2024, CNAN received a MOTOR Top 20 Award from MOTOR Information Systems for our electric vehicle service contract. We have been named a #1 provider 22 times in the Dealers’ Choice Awards. In addition, CNAN was the first and one of only two service contract companies recognized for “Highest Overall Dealer Satisfaction” by J.D. Power and Associates. We are a wholly owned subsidiary of CNA Financial, one of the nation’s oldest and largest commercial insurers with more than $60 billion in assets.