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Temporary Data Engineer Jobs in California (NOW HIRING)

E*Pro, Inc.

Big Data Developer

San Jose, CA · On-site

$62 - $80.50/hr

... Temp-to-Hire. In addition, our industry expertise and knowledge within financial services ... Hadoop Big Data Technologies HBase Linux Core Java Mongo DB Big Data Architecture knowledge is ...

AllSTEM Connections

Data Analyst IV

San Francisco, CA · On-site

$187K - $220K/yr

Key Responsibilities Technical Execution & Systems Engineering • Lakehouse Development: Design ... For temporary assignments lasting 13 weeks or longer, AllSTEM Connections is pleased to offer major ...

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All JobsData Engineer JobsTemporary Data Engineer JobsTemporary Data Engineer Jobs in California

Temporary Data Engineer information

See California salary details

$43.9K

$128K

$175.2K

How much do temporary data engineer jobs pay per year?

As of Jul 19, 2026, the average yearly pay for temporary data engineer in California is $128,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $135,700.00 per year, depending on experience, location, and employer.

What are the typical daily responsibilities of a Temporary Data Engineer?

As a Temporary Data Engineer, your day-to-day work often involves designing and maintaining data pipelines, cleaning and validating data, and implementing ETL processes to support business analytics or project objectives. You'll collaborate with data scientists, analysts, and other engineers to ensure data accuracy and system reliability, while troubleshooting issues or optimizing workflows as needs arise. Since this is a temporary role, you may also take on specialized short-term projects or support urgent business initiatives where fast, high-quality results are essential. The work environment is usually fast-paced, making adaptability and teamwork especially important for success.

What is a Temporary Data Engineer job?

A Temporary Data Engineer is a short-term role responsible for designing, building, and maintaining data pipelines and infrastructure. These professionals help organizations collect, store, and process data efficiently, often working on specific projects or to support peak workloads. Temporary Data Engineers typically use SQL, Python, and cloud platforms to manage data workflows. The role may last for weeks or months, depending on the company's needs.

What are the key skills and qualifications needed to thrive in the Temporary Data Engineer position, and why are they important?

To thrive as a Temporary Data Engineer, you need a solid grasp of data modeling, ETL processes, and SQL or other database languages, often supported by a degree in computer science or a related field. Familiarity with cloud platforms like AWS or Azure, experience with big data frameworks such as Apache Spark, and possibly certifications like Google Professional Data Engineer are valuable. Strong problem-solving skills, the ability to quickly adapt to new environments, and effective communication are important soft skills in this role. These abilities are crucial because Temporary Data Engineers must rapidly contribute to projects, ensure data systems run smoothly, and collaborate efficiently during short-term assignments.

What are the most commonly searched types of Data Engineer jobs in California? The most popular types of Data Engineer jobs in California are:
What are popular job titles related to Temporary Data Engineer jobs in California? For Temporary Data Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Temporary Data Engineer jobs in California look for? The top searched job categories for Temporary Data Engineer jobs in California are:
What cities in California are hiring for Temporary Data Engineer jobs? Cities in California with the most Temporary Data Engineer job openings:
Temporary Data Engineer jobs near you
Infographic showing various Temporary Data Engineer job openings in California as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $128,018 per year, or $61.5 per hour.
Staff Engineer, Data Analysis (R5290)

Staff Engineer, Data Analysis (R5290)

Shield AI

San Diego, CA

$150K - $220K/yr

Full-time

Posted 5 days ago

New

Job description

Founded in 2015, Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software and V-BAT and X-BAT aircraft. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

Job Description:

We're looking for a Staff Engineer to lead V-BAT's fleet data analysis efforts. The V-BAT system produces rich data from real-world flight tests, fielded aircraft, production activity, and simulation runs.  

You will own the analysis pipelines, tooling, standards, and metrics that help the team understand fleet-wide system performance derived from information from software and hardware systems. You will facilitate deep studies into flight-critical sensor performance, navigation, communications, and other key aircraft behaviors. You will work closely with DevOps, Flight Software, Flight Test, Production, Quality, and Operations teams to turn complex aircraft data into actionable engineering insight. 

What you'll do:
  • Lead the technical strategy for V-BAT fleet data analysis across fielded aircraft, flight test, simulation, production, and quality workflows 
  • Own and improve the pipelines that transform raw flight, simulation, and fleet data into reliable engineering metrics, reports, and analysis products 
  • Conduct fleet-wide studies to identify trends in hardware quality, system performance, reliability, and operational behavior 
  • Analyze flight-critical sensor performance, GNSS-denied navigation performance, communications behavior, and other aircraft subsystems that are critical to mission success 
  • Standardize the team's analysis methods across online tools, Jupyter notebooks, automated Python scripts, and legacy Matlab workflows 
  • Define best practices for analysis methods, data review, documentation, validation, reproducibility, and contribution workflows 
  • Build automated Python workflows that make high-value metrics easily accessible to engineering, production, quality, and leadership teams 
  • Partner with DevOps to build, deploy, maintain, and scale the infrastructure required for automated analysis pipelines and dashboards 
  • Work with Software, GNC, Embedded, Flight Test, Systems, Production, Quality, and Operations teams to define metrics that reflect aircraft performance and product health 
  • Support anomaly investigations, root-cause analysis, release readiness, production quality improvements, and customer-impacting fleet investigations with rigorous data analysis 
  • Mentor engineers on effective data analysis practices and raise the quality bar for data-driven engineering decisions across the V-BAT team 
Required qualifications:
  • 5+ years of relevant experience with a Bachelor's degree in Computer Science, Data Science, or a related technical field 
  • Strong Python skills and experience building data analysis tools, automated analysis workflows, or data pipelines 
  • Experience analyzing data from fielded physical products such as aerospace systems, automotive systems, robotics platforms, commercial electronics, IoT devices, industrial equipment, or similarly complex real-world systems 
  • Experience working with large, messy datasets from deployed products, test events, simulations, production systems, or operational environments 
  • Ability to translate ambiguous engineering questions into structured analysis, sound conclusions, and clear recommendations 
  • Strong communication skills and the ability to influence cross-functional engineering, production, quality, and operations teams 
Preferred qualifications:
  • Experience with flight test data, aircraft telemetry, UAVs, robotics, autonomy, embedded systems, GNC, navigation systems, communications systems, or aerospace sensor suites 
  • Experience with Matlab, Jupyter, or similar analysis and visualization tools 
  • Experience building production-quality dashboards, automated reports, data products, or fleet-health monitoring systems 
  • Experience with databases, cloud storage, data lake architectures, time-series databases, telemetry systems, or data cataloging 
  • Experience with anomaly detection, trend analysis, statistical process control, reliability analysis, regression detection, or automated validation of complex systems 
$150,000 - $220,000 a year
#LI-SM1
#LD

Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
 
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
 
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
 
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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