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Data Engineer Jobs in Florence, AZ (NOW HIRING)

GCP Architect

Chandler, AZ · Remote

$65.25 - $84/hr

Secaucus, NJ/Remote Duration: 1 Years JD: 8+ years of experience in Data Engineering or L3 level of support in data Analytics General Description Experience with Data Lake, data warehouse ETL ...

Partner with data engineering, IT, and business teams to develop scalable data pipelines and deploy machine learning models into production environments. * Evaluate data quality, model performance ...

Data Center Design Engineer Chandler, AZ Hybrid (3 Days in 2 Days remote) 12-24 Month Contract Description We are seeking experienced Data Center Infrastructure Design Engineers to support the design ...

Showing results 21-40

Data Engineer information

See Florence, AZ salary details

$41.6K

$121.4K

$166.1K

How much do data engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for data engineer in Florence, AZ is $121,362.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,100.00 and $128,600.00 per year, depending on experience, location, and employer.

What is a data engineer?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

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 a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What does a data engineer do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

How do data engineers typically collaborate with data scientists and analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipeline tools. Entry-level positions may be available for those with relevant internships or strong foundational skills, but most data engineering roles demand several years of experience or advanced knowledge of tools like SQL, Python, and cloud platforms.

What is the role of a data engineer?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and store 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 cities near Florence, AZ are hiring for Data Engineer jobs?

Cities near Florence, AZ with the most Data Engineer job openings:

Infographic showing various Data Engineer job openings in Florence, AZ as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 15% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $121,362 per year, or $58.3 per hour.

Cyber AI Data Engineer Senior Consultant

Deloitte

Gilbert, AZ • On-site

Full-time

Re-posted 21 days ago


Key responsibilities

  • Build and operate governed data pipelines and services that support risk reporting, continuous controls monitoring, and AI-assisted security operations.

  • Design data models for risk and controls domains, enabling self-service analytics and dashboards.

  • Implement data quality checks, lineage, metadata, and access controls to support auditability and regulatory compliance.


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

47th of 154 rated financial services


Job description

Are you interested in improving the cyber and organizational risk profiles of leading companies? Do you want to build the data foundations that power the next generation of AI-enabled cyber defense?

If yes, then Deloitte's Cyber team could be the place for you.

We are looking for a hands-on Data Engineer to build and operate the governed data foundations powering cyber risk, compliance evidence, and agentic AI-enabled cyber workflows. You will design production-grade pipelines and services that support risk reporting, continuous controls monitoring, and AI-assisted security operations-built with strong governance, lineage, privacy-by-design, and audit-ready evidence.

This role is ideal for engineers who can bridge modern data engineering and software development with Governance, Risk, and Compliance (GRC) expectations in regulated enterprise environments.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Senior Consultant, Strategy, Growth and Transformation on the Cyber team, you will be responsible for:

  • Building scalable batch and stream processing pipelines that ingest security telemetry, control evidence, and compliance artifacts into governed data stores.
  • Designing data models for risk and controls domains, including key risk indicators, issues and defects, risk acceptance, control testing outcomes, audit evidence, and policy exceptions, and enabling self-service analytics and dashboards.
  • Implementing data quality checks, lineage, metadata, and access controls to support auditability, regulatory defensibility, and repeatable evidence generation.
  • Developing AI-enabled capabilities that accelerate governance, risk, and compliance and cyber operations, including evidence summarization, control testing assist, policy question-and-answer, investigation copilots, ticket triage, and exception reasoning using agentic patterns, workflow orchestration, and retrieval-augmented generation.
  • Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces, event patterns, and connectors, with observability and runbooks for production support.
  • Partnering with Cyber, Risk, Compliance, Privacy, and Legal stakeholders to translate requirements into implementable controls and developer-ready guardrails.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

You will join a cyber engineering team focused on enabling resilient, secure, and compliant operations through modern data platforms and AI-enabled automation. The team builds repeatable assets-reference architectures, accelerators, and governance patterns-to help clients modernize and scale cyber and GRC programs.

Qualifications

Required:

  • Bachelor's degree or equivalent practical experience.
  • 4+ years of experience in data engineering and software development using Python and SQL.
  • Experience building production data pipelines and data models for batch processing, stream processing, or both, and deploying solutions using cloud platforms, containers, infrastructure as code, application programming interfaces, and secrets management.
  • Experience implementing data governance controls including data classification, personally identifiable information handling, least-privilege access, encryption, secrets management, retention, audit logging, and lineage or metadata management.
  • Experience supporting governance, risk, and compliance workflows, including risk reporting, audit data requests, controls monitoring, controls testing, compliance metrics, governance, risk, and compliance tool integrations, and large language model-enabled applications using retrieval-augmented generation, vector or hybrid retrieval, tool or function calling, evaluation or monitoring, prompt-injection defenses, and secure access patterns.
  • Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience in consulting or a Big 4 environment.
  • Experience with Java, Go, or JavaScript.
  • Experience integrating with ServiceNow GRC, Archer, OneTrust, or BigID and building evidence pipelines mapped to control objectives.
  • Experience building pipelines for security information and event management, security orchestration, automation, and response, vulnerability, identity, or cloud security posture data.
  • Experience operationalizing large language model operations or machine learning operations capabilities, including evaluation, monitoring, versioning, and governance workflows.
  • Security certification such as CompTIA Security+, Certified Information Security Manager, Certified Information Systems Auditor, Certified Information Systems Security Professional, or a cloud certification.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400 to $207,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


#CyberDTP27

Qualifications:

Are you interested in improving the cyber and organizational risk profiles of leading companies? Do you want to build the data foundations that power the next generation of AI-enabled cyber defense?

If yes, then Deloitte's Cyber team could be the place for you.

We are looking for a hands-on Data Engineer to build and operate the governed data foundations powering cyber risk, compliance evidence, and agentic AI-enabled cyber workflows. You will design production-grade pipelines and services that support risk reporting, continuous controls monitoring, and AI-assisted security operations-built with strong governance, lineage, privacy-by-design, and audit-ready evidence.

This role is ideal for engineers who can bridge modern data engineering and software development with Governance, Risk, and Compliance (GRC) expectations in regulated enterprise environments.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Senior Consultant, Strategy, Growth and Transformation on the Cyber team, you will be responsible for:

  • Building scalable batch and stream processing pipelines that ingest security telemetry, control evidence, and compliance artifacts into governed data stores.
  • Designing data models for risk and controls domains, including key risk indicators, issues and defects, risk acceptance, control testing outcomes, audit evidence, and policy exceptions, and enabling self-service analytics and dashboards.
  • Implementing data quality checks, lineage, metadata, and access controls to support auditability, regulatory defensibility, and repeatable evidence generation.
  • Developing AI-enabled capabilities that accelerate governance, risk, and compliance and cyber operations, including evidence summarization, control testing assist, policy question-and-answer, investigation copilots, ticket triage, and exception reasoning using agentic patterns, workflow orchestration, and retrieval-augmented generation.
  • Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces, event patterns, and connectors, with observability and runbooks for production support.
  • Partnering with Cyber, Risk, Compliance, Privacy, and Legal stakeholders to translate requirements into implementable controls and developer-ready guardrails.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

You will join a cyber engineering team focused on enabling resilient, secure, and compliant operations through modern data platforms and AI-enabled automation. The team builds repeatable assets-reference architectures, accelerators, and governance patterns-to help clients modernize and scale cyber and GRC programs.

Qualifications

Required:

  • Bachelor's degree or equivalent practical experience.
  • 4+ years of experience in data engineering and software development using Python and SQL.
  • Experience building production data pipelines and data models for batch processing, stream processing, or both, and deploying solutions using cloud platforms, containers, infrastructure as code, application programming interfaces, and secrets management.
  • Experience implementing data governance controls including data classification, personally identifiable information handling, least-privilege access, encryption, secrets management, retention, audit logging, and lineage or metadata management.
  • Experience supporting governance, risk, and compliance workflows, including risk reporting, audit data requests, controls monitoring, controls testing, compliance metrics, governance, risk, and compliance tool integrations, and large language model-enabled applications using retrieval-augmented generation, vector or hybrid retrieval, tool or function calling, evaluation or monitoring, prompt-injection defenses, and secure access patterns.
  • Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience in consulting or a Big 4 environment.
  • Experience with Java, Go, or JavaScript.
  • Experience integrating with ServiceNow GRC, Archer, OneTrust, or BigID and building evidence pipelines mapped to control objectives.
  • Experience building pipelines for security information and event management, security orchestration, automation, and response, vulnerability, identity, or cloud security posture data.
  • Experience operationalizing large language model operations or machine learning operations capabilities, including evaluation, monitoring, versioning, and governance workflows.
  • Security certification such as CompTIA Security+, Certified Information Security Manager, Certified Information Systems Auditor, Certified Information Systems Security Professional, or a cloud certification.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400 to $207,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


#CyberDTP27

Education:Bachelor's DegreeEmployment Type:

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