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Automotive Data Engineer Jobs in Arizona (NOW HIRING)

Senior Data Engineer

Mesa, AZ · Remote

$105K - $142K/yr

... process control, automotive manufacturing, heavy equipment, wireless base stations, and ... Collaborate with developers, and business stakeholders to understand data requirements and ...

Senior Data Engineer, Predictive Modeling

Tempe, AZ · On-site

$101K - $137K/yr

... automotive retailer in history. We expanded nationally, went public on the New York Stock Exchange ... We're not just building data pipelines; we're engineering intelligent systems that predict the ...

... automotive retailer in history. We expanded nationally, went public on the New York Stock Exchange ... We're not just building data pipelines; we're engineering intelligent systems that predict the ...

Senior Data Engineer, Predictive Modeling

Tempe, AZ · On-site

$101K - $137K/yr

... automotive retailer in history. We expanded nationally, went public on the New York Stock Exchange ... We're not just building data pipelines; we're engineering intelligent systems that predict the ...

As a Texas Instruments Product Engineer, you will have the opportunity to work in a vibrant and ... automotive, data center, personal electronics and communications equipment. At our core, we have a ...

As a Texas Instruments Product Engineer, you will have the opportunity to work in a vibrant and ... automotive, data center, personal electronics and communications equipment. At our core, we have a ...

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Automotive Data Engineer information

What is an automotive data engineer?

An Automotive Data Engineer is a professional who designs, develops, and manages systems for collecting, processing, and analyzing data generated by vehicles and automotive systems. They work with large datasets from sources such as sensors, telematics, and onboard diagnostics to improve vehicle performance, safety, and efficiency. Their role often involves collaborating with software developers, data scientists, and automotive engineers to build data-driven solutions for connected and autonomous vehicles.

What key skills and qualifications are needed to thrive as an automotive data engineer?

To thrive as an Automotive Data Engineer, you need expertise in data analytics, programming (often Python or SQL), and a strong understanding of automotive systems, typically supported by a degree in computer science, engineering, or a related field. Familiarity with big data platforms (like Hadoop or Spark), automotive communication protocols (such as CAN or LIN), and certifications in data engineering or cloud technologies are highly valued. Strong problem-solving abilities, teamwork, and effective communication help distinguish top performers in this role. These skills are crucial for developing reliable data-driven solutions that enhance vehicle performance, safety, and innovation in a rapidly evolving automotive industry.

What are some common challenges automotive data engineers face when working with vehicle data?

Automotive Data Engineers often encounter challenges related to the sheer volume and complexity of data generated by modern vehicles, including sensor, telematics, and diagnostic information. Integrating data from various sources and ensuring its quality, consistency, and security can be demanding. Additionally, collaborating with cross-functional teams—such as software developers, data scientists, and automotive engineers—requires strong communication skills to align technical requirements and project goals. Adapting to evolving automotive technologies and compliance standards is also crucial for success in this role.

What is the difference between Automotive Data Engineer vs Data Scientist in the automotive industry?

AspectAutomotive Data EngineerData Scientist
Required CredentialsBachelor's in Computer Science, Data Engineering, or related field; experience with SQL, Python, big data toolsBachelor's or Master's in Data Science, Statistics, or related; proficiency in Python, R, machine learning
Work EnvironmentAutomotive companies, tech firms, data infrastructure teamsResearch labs, automotive R&D, analytics teams
Employer & Industry UsageFocus on building data pipelines, managing data infrastructure in automotive settingsFocus on analyzing data, creating models for vehicle performance, customer insights

Automotive Data Engineers primarily develop and maintain data infrastructure within the automotive industry, ensuring data flows efficiently. Data Scientists analyze this data to generate insights and predictive models. Both roles often collaborate but focus on different aspects of data management and analysis.

What are popular job titles related to Automotive Data Engineer jobs in Arizona?

For Automotive Data Engineer jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Automotive Data Engineer jobs in Arizona look for?

The top searched job categories for Automotive Data Engineer jobs in Arizona are:

What cities in Arizona are hiring for Automotive Data Engineer jobs?

Cities in Arizona with the most Automotive Data Engineer job openings:

Senior Data Engineer

amphenol

Mesa, AZ • Remote

$105K - $142K/yr

Part-time

Posted 11 days ago


Job description

Job Description Summary:

Amphenol Industrial Operations is seeking a highly skilled and motivated Senior Data Engineer to lead the design, development, and optimization of enterprise data solutions that support manufacturing operations, business intelligence, and strategic decision-making across our global organization. This role is responsible for building and maintaining scalable, secure, and high-performance data pipelines and infrastructure that transform data from ERP systems, manufacturing applications, cloud platforms, remote databases, and other business systems into trusted and actionable information.

Company Introduction:

Amphenol Industrial Operations, headquartered in Endicott, New York with global manufacturing, sales and marketing locations, specializes in delivering a comprehensive range of high-reliability power and signal connectors along with interconnection systems designed specifically for industrial applications. Our solutions cater to diverse industrial sectors such as alternative energy, power generation and storage, rail and mass transit, process control, automotive manufacturing, heavy equipment, wireless base stations, and petrochemical industries.                                                                                                         

Our product portfolio encompasses power interconnects utilizing RADSOK® contact technology, ruggedized military derivative commercial cylindrical connectors such as AC Threaded (SAE AS50151 style), PT (MIL-DTL-26482 style) and GT reverse bayonet style, assemblies and harnesses using these and other industry standard interconnect. With a dedicated team of over 900 skilled professionals and certifications including ISO9001 and IATF 16949, Amphenol Industrial Operations consistently meets the highest standards of quality and performance.                                                                                                                        

Amphenol Industrial Operations proudly operates as a division of Amphenol Corporation, headquartered in Wallingford, Connecticut.

Duties/Responsibilities:

  • Design and implement robust, scalable ETL/ELT pipelines across multiple SQL Server environments and cloud platforms.
  • Collaborate with developers, and business stakeholders to understand data requirements and translate them into technical solutions.
  • Develops and maintains comprehensive documentation of data processes, reports, applications, and procedures to ensure consistency, knowledge sharing, and alignment with organizational standards.
  • Ensure data quality, integrity, and security through validation, monitoring, and governance practices.
  • Maintain and evolve data models, schemas, and metadata for analytics and reporting.
  • Designs, develops, and deploys scalable reporting and dashboard solutions to support business intelligence, data visualization, and operational efficiency, ensuring appropriate security measures.
    Troubleshoot and resolve data issues, ensuring high availability and performance of data systems.
  • Integrate data from a variety of business systems including ERP, SharePoint, external systems.
  • Design, implement, and maintain secure cross-region data integration processes to extract data from remote databases in China and Turkey, validate and transform it, and consolidate it into the U.S.-based ERP database while ensuring data integrity, reliability, performance, and compliance with organizational security standards.
  • Optimize SQL queries, stored procedures, indexes, database objects, and data-loading processes to improve performance, scalability, and resource utilization.
  • Monitor scheduled data pipelines, database jobs, and integration processes; implement logging, alerting, retry mechanisms, and exception handling to identify and resolve failures promptly.

Qualifications - Education/Experience:

  • Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or a related discipline.
  • 6+ years of professional data engineering experience.
  • Strong experience designing, developing, and supporting production data pipelines.
  • Strong understanding of:
    • Data engineering principles
    • Data modeling
    • ETL/ELT development
    • Data quality management
    • Enterprise reporting and analytics
  • Experience working with large datasets and complex data structures.
  • Strong analytical and problem-solving skills.
  • Advanced experience with Microsoft SQL Server, including T-SQL, stored procedures, views, functions, indexing, query optimization, execution plans, and performance troubleshooting.
  • Demonstrated experience designing, developing, and supporting ETL/ELT pipelines across multiple databases, business systems, and geographic regions.
  •  Experience developing reports, dashboards, and business intelligence solutions using tools such as Power BI, SQL Server Reporting Services, or equivalent reporting platforms.

Knowledge/Skills:

  • Knowledge of ETL/ELT development concepts, including data extraction, transformation, incremental loading, scheduling, dependency management, and error recovery.
  • Strong knowledge of data engineering principles, architectures, design patterns, and industry best practices.
  • Strong understanding of relational data modeling, database normalization, dimensional modeling, data warehousing, and metadata management.
  • Knowledge of ETL/ELT development concepts, including data extraction, transformation, incremental loading, scheduling, dependency management, and error recovery.
  •  Strong understanding of data quality management, including validation, reconciliation, completeness checks, duplicate prevention, auditing, and exception handling.
  • Ability to integrate data from ERP systems, SharePoint, APIs, flat files, external applications, cloud platforms, and remote databases.