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Temporary Amazon Data Engineer Jobs in California

IT America Inc

Sr. Data Engineer (AI + AWS)

Irvine, CA · On-site

$122K - $147K/yr

Position: Sr. Data Engineer (AI + AWS) Location: Irvine/LA, CA (Onsite) Duration: Long term ... Experience with AWS AI services such as Amazon SageMaker, Bedrock, or Amazon OpenSearch is ...

Staffingine LLC

AWS Data Engineer

San Francisco, CA · On-site

$134K - $162K/yr

AWS Data Engineer Job Location: San Francisco, CA Job Type ... Contract * 7+ years of experience in Amazon Web Services (AWS) Cloud Computing * Strong background ...

Mill

Data Engineer - Data Platform

San Bruno, CA · On-site

$185K - $210K/yr

The Role As a Data Engineer at Mill, you'll build and maintain the core data infrastructure that ... Experience working with transactional databases (e.g., PostgreSQL, Amazon RDS) as a data source ...

Mill

Data Engineer - Data Platform

San Bruno, CA · On-site

$185K - $210K/yr

The Role As a Data Engineer at Mill, you'll build and maintain the core data infrastructure that ... Experience working with transactional databases (e.g., PostgreSQL, Amazon RDS) as a data source ...

PlayStation Global

Data Engineer II

Aliso Viejo, CA · Remote

$122K - $146K/yr

Data Engineer IIAliso Viejo, CA The Data Engineering Team fuels real-time, intelligent data ... Experience with Amazon Web Services at enterprise scale including, but not limited to, OpenSearch ...

Centerfield

Data Engineer

Los Angeles, CA · On-site

$100K - $130K/yr

As a Data Engineer , you'll help design the highly specialized data collection infrastructure in ... Amazon Web Services, including S3, SQS, Redshift, and DocumentDB Life at Centerfield... * This is a ...

New

Mill

Data Engineer - Data Platform

San Bruno, CA · On-site

$185K - $210K/yr

The Role As a Data Engineer at Mill, you'll build and maintain the core data infrastructure that ... Experience working with transactional databases (e.g., PostgreSQL, Amazon RDS) as a data source ...

Samsung Electronics

Sr. Data Engineer

Mountain View, CA · On-site

$170K - $210K/yr

Position Summary Sr Data Engineer - Samsung Ads About Samsung Ads: Samsung Ads is a fast-growing ... Experience with cloud platforms, particularly Amazon Web Services (AWS) Background in digital ...

Mill

Data Engineer - Data Platform

San Bruno, CA · On-site

$185K - $210K/yr

The Role As a Data Engineer at Mill, you'll build and maintain the core data infrastructure that ... Experience working with transactional databases (e.g., PostgreSQL, Amazon RDS) as a data source ...

AllSTEM Connections

Data Engineer

San Francisco, CA · On-site

$120K - $133K/yr

Lead Data Engineer (GCP, Supply Chain & AI Data Platforms) Role Overview We are seeking an ... For temporary assignments lasting 13 weeks or longer, AllSTEM Connections is pleased to offer major ...

INFOTRON

Senior Data Engineer

Berkeley, CA · On-site

$140 - $190/hr

Senior Data Engineer Location: Berkeley, CA (Onsite - 5 Days/Week) Employment Type: Contract ... or Amazon QuickSight is an advantage. What We're Looking For * Strong analytical and ...

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Showing results 21-40

All JobsAmazon Data Engineer JobsTemporary Amazon Data Engineer JobsTemporary Amazon Data Engineer Jobs in California

Temporary Amazon Data Engineer information

What does a temporary Amazon data engineer do?

A Temporary Amazon Data Engineer is responsible for designing, building, and maintaining data pipelines and systems within Amazon on a short-term or contract basis. They work with large datasets, ensure data quality, and collaborate with other teams to support analytics and business intelligence initiatives. Their role includes tasks such as data extraction, transformation, and loading (ETL), as well as troubleshooting data issues and optimizing data workflows. Although the position is temporary, it often requires strong technical skills in SQL, Python, and cloud services like AWS. The work helps Amazon make data-driven decisions and improve its services.

What are the key skills and qualifications needed to thrive as a temporary Amazon data engineer?

To thrive as a Temporary Amazon Data Engineer, you need strong proficiency in data modeling, SQL, and programming languages such as Python or Java, typically supported by a degree in computer science or a related field. Familiarity with Amazon Web Services (AWS) data tools like Redshift, S3, Glue, and ETL pipelines, as well as relevant certifications like AWS Certified Data Analytics, is highly valuable. Excellent problem-solving skills, adaptability, and effective communication are crucial soft skills for collaborating on short-term projects and delivering timely results. These skills and qualifications ensure efficient data solutions, seamless integration with Amazon's platforms, and the ability to meet dynamic business needs in a fast-paced environment.

What are some common challenges temporary Amazon data engineers face when onboarding to new projects?

Temporary Amazon Data Engineers often encounter challenges such as quickly adapting to existing data infrastructure, understanding proprietary tools and processes, and integrating with teams that may already have established workflows. Since the role is time-limited, it’s crucial to rapidly build relationships with stakeholders and clarify project goals early on. Proactive communication and leveraging available documentation can help overcome these hurdles, ensuring a smoother transition and effective project delivery.

What is the difference between Temporary Amazon Data Engineer vs Temporary Google Data Engineer?

AspectTemporary Amazon Data EngineerTemporary Google Data Engineer
Required CredentialsBachelor's in CS, Data Engineering certifications, AWS knowledgeBachelor's in CS, Data Engineering certifications, GCP knowledge
Work EnvironmentAmazon's cloud infrastructure, e-commerce, and logisticsGoogle Cloud Platform, advertising, and tech services
Employer & Industry UsageAmazon, retail, logistics, cloud servicesGoogle, tech, advertising, cloud services
Search & Comparison IntentHigh overlap in cloud data roles, certifications, and industrySimilar roles in cloud data engineering, but with different platform focus

Temporary Amazon Data Engineers and Temporary Google Data Engineers share similar skills, certifications, and work environments focused on cloud data platforms. The main difference lies in the cloud platform expertise—AWS for Amazon and GCP for Google—making each role suited to specific employer ecosystems and industry applications.

What are the most commonly searched types of Amazon Data Engineer jobs in California?

The most popular types of Amazon Data Engineer jobs in California are:

What are popular job titles related to Temporary Amazon Data Engineer jobs in California?

For Temporary Amazon Data Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Temporary Amazon Data Engineer jobs in California look for?

The top searched job categories for Temporary Amazon Data Engineer jobs in California are:

What cities in California are hiring for Temporary Amazon Data Engineer jobs?

Cities in California with the most Temporary Amazon Data Engineer job openings:

Temporary Amazon Data Engineer jobs near you
Infographic showing various Temporary Amazon Data Engineer job openings in California as of June 2026, with employment types broken down into 92% Full Time, 5% Part Time, 1% Temporary, and 2% Contract. Highlights an 99% Physical, and 1% Remote job distribution.

Sr. Data Engineer (AI + AWS)

IT America Inc

Irvine, CA • On-site

$122K - $147K/yr

Contractor

Re-posted 22 days ago

Job description

Position: Sr. Data Engineer (AI + AWS)

Location: Irvine/LA, CA  (Onsite)

Duration: Long term contract

Job Summary:

We are seeking a highly skilled Data Engineer with expertise in AI-enabled data platforms, AWS cloud services, Python, PySpark, and Kubernetes to design, develop, and optimize scalable data pipelines and machine learning data infrastructure. The ideal candidate will have experience building cloud-native data solutions, processing large-scale datasets, and supporting AI/ML workloads in AWS environments.

Key Responsibilities:

  • Design, build, and maintain scalable ETL/ELT data pipelines using Python and PySpark.
  • Develop cloud-native data solutions utilizing AWS services such as S3, EMR, Glue, Lambda, Redshift, Athena, ECS/EKS, IAM, CloudWatch, and Step Functions.
  • Build and optimize data ingestion frameworks for structured, semi-structured, and streaming data.
  • Collaborate with Data Scientists and AI Engineers to prepare, transform, and deliver high-quality datasets for AI/ML model training and inference.
  • Deploy and manage containerized data applications using Kubernetes (EKS) and Docker.
  • Develop data processing workflows using Spark and optimize performance for large-scale distributed processing.
  • Design data lakes and modern data architectures following AWS best practices.
  • Implement data quality checks, monitoring, logging, and alerting mechanisms.
  • Optimize SQL queries and data models for analytical workloads.
  • Build CI/CD pipelines for automated deployment of data engineering solutions.
  • Ensure data governance, security, compliance, and access controls across cloud environments.
  • Troubleshoot production issues and provide performance tuning for distributed data systems.
  • Work closely with cross-functional teams in Agile/Scrum environments.

Required Qualifications:

  • Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or related field.
  • 10+ years of Data Engineering experience.
  • Strong programming experience in Python.
  • Hands-on expertise with PySpark and Apache Spark.
  • Strong experience with AWS Cloud services.
  • Experience with Kubernetes (EKS) and Docker.
  • Strong SQL skills and experience with relational databases.
  • Experience building scalable ETL/ELT pipelines.
  • Familiarity with Git and CI/CD practices.
  • Excellent analytical, debugging, and problem-solving skills.

Required Technical Skills:

  • Cloud: AWS (S3, Glue, EMR, Lambda, Redshift, Athena, ECS/EKS, IAM, CloudWatch, Step Functions)
  • Programming: Python
  • Big Data: PySpark, Apache Spark
  • Containers: Kubernetes, Docker
  • Databases: PostgreSQL, MySQL, SQL Server, Redshift
  • Data Storage: Data Lake, Data Warehouse
  • Version Control: Git
  • Operating Systems: Linux
  • Methodology: Agile/Scrum

AI/ML Experience:

  • Support AI/ML data pipelines and feature engineering.
  • Prepare datasets for model training and inference.
  • Experience integrating ML workflows into cloud-based data platforms.
  • Familiarity with LLMs, Generative AI, Vector Databases, or Retrieval-Augmented Generation (RAG) is a plus.
  • Experience with AWS AI services such as Amazon SageMaker, Bedrock, or Amazon OpenSearch is preferred.

Preferred Qualifications:

  • Experience with Apache Airflow or AWS Managed Workflows (MWAA).
  • Knowledge of Kafka or Kinesis for streaming data.
  • Experience with Delta Lake, Iceberg, or Apache Hudi.
  • Infrastructure-as-Code experience using Terraform or CloudFormation.
  • AWS certifications (Solutions Architect, Data Engineer, or Machine Learning Specialty) are highly desirable.