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Quantitative Data Engineer Jobs in California (NOW HIRING)

Triumph

Senior Data Engineer

San Francisco, CA · On-site

$124K - $169K/yr

As the first dedicated data engineering hire, you'll own the full data stack, including ingestion, transformation, and pipeline reliability, while collaborating with both quantitative strategy and ...

Brex

Data Engineer

San Francisco, CA · On-site

$120K - $151K/yr

Data at Brex Our Scientists and Engineers work together to make data - and insights derived from ... Exceptional quantitative and analytical skills. * Strong communication skills and ability to ...

Triumph

Senior Data Engineer

San Francisco, CA · On-site

$200K - $400K/yr

You'll work at the intersection of a quantitative strategy team and a fast-moving engineering org, building the foundation that both depend on. What You'll Do * Architect and own the data warehouse.

Triumph Arcade, Inc

Senior Data Engineer

San Francisco, CA · On-site

$200K - $400K/yr

You'll work at the intersection of a quantitative strategy team and a fast-moving engineering org, building the foundation that both depend on. What You'll Do * Architect and own the data warehouse.

Apple

Machine Learning Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

... quantitative and qualitative data. Experience operating within global data privacy frameworks (e.g ... Experience with prompt engineering, machine learning tools, and fine-tuning Large Language Models ...

Glow Networks

Data Analyst

Mountain View, CA · On-site

Bachelor's degree in a quantitative field - Computer Science, Mathematics, Engineering or related fields; Master's preferred. * 6-9 years of work experience involving quantitative data analysis.

Adobe

Data Science Engineer

San Francisco, CA

$134K - $162K/yr

Capture, synthesize, and interpret disparate quantitative data within the context of ... engineering preferred, or related work experience * Knowledge of Microsoft Office, specifically ...

Adobe

Data Science Engineer

San Jose, CA

$134K - $161K/yr

Capture, synthesize, and interpret disparate quantitative data within the context of ... engineering preferred, or related work experience * Knowledge of Microsoft Office, specifically ...

TSW Core LLC

Senior Data Engineer

Palo Alto, CA · On-site

$124K - $169K/yr

Proficiency with quantitative and statistical methods to solve analytical problems and build models ... Extensive data engineering experience combined with strong business acumen in the E-commerce domain ...

Nuna Inc.

Lead Data Engineer

San Francisco, CA · On-site

$180K - $225K/yr

Degree in a quantitative field (data science, economics, statistics, engineering, or similar) * Experience with SDLC and managing machine learning models in production (MLOps) Nuna is an Equal ...

Apple Inc.

Machine Learning Data Engineer

Cupertino, CA · On-site

$184.70 - $324.80/hr

... from quantitative and qualitative data. * Experience operating within global data privacy ... Experience with prompt engineering, machine learning tools, and fine-tuning Large Language Models ...

Glidewell Dental

Data Engineer III

Irvine, CA

$119K - $160K/yr

Analyze data to discover and interpret trends, patterns, and relationships * Responsible for the ... Bachelor's degree in Mathematics, Statistics, or other quantitative field * 5+ years of relevant ...

Apple

Machine Learning Data Engineer

Cupertino, CA

$184K - $324K/yr

... quantitative and qualitative data. Experience operating within global data privacy frameworks (e.g ... Experience with prompt engineering, machine learning tools, and fine-tuning Large Language Models ...

Anaheimducks

Lead Data Engineer

Anaheim, CA · On-site

$140K - $180K/yr

Lead Data Engineer Pay Details: The annual base salary range for this position in California is ... Academic background in a quantitative or technical field such as physics, mathematics, computer ...

OC Sports and Entertainment

Lead Data Engineer

Anaheim, CA · On-site

$140K - $180K/yr

Lead Data Engineer Pay Details: The annual base salary range for this position in California is ... Academic background in a quantitative or technical field such as physics, mathematics, computer ...

OCVIBE

Lead Data Engineer

Anaheim, CA · On-site

$140K - $180K/yr

Lead Data Engineer Pay Details: The annual base salary range for this position in California is ... Academic background in a quantitative or technical field such as physics, mathematics, computer ...

OC Sports and Entertainment

Lead Data Engineer

Anaheim, CA · On-site

$140K - $180K/yr

Lead Data Engineer Pay Details: The annual base salary range for this position in California is ... Academic background in a quantitative or technical field such as physics, mathematics, computer ...

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Quantitative Data Engineer information

What are the key skills and qualifications needed to thrive as a quantitative data engineer, and why are they important?

To excel as a Quantitative Data Engineer, you need strong proficiency in programming (such as Python, R, or C++), advanced mathematical and statistical knowledge, and a relevant degree in computer science, mathematics, or a related field. Experience with big data tools (like Spark, Hadoop), cloud platforms, and data pipeline systems, as well as familiarity with financial data sets, is typically required. Analytical thinking, detail orientation, and effective problem-solving skills distinguish top performers in this role. These competencies are critical for efficiently transforming complex data into actionable insights and supporting robust quantitative models in data-driven environments.

What is a quantitative data engineer?

A Quantitative Data Engineer is a professional who designs, builds, and maintains data infrastructure that supports quantitative analysis, typically in finance or technology sectors. They work closely with quantitative analysts and data scientists to ensure efficient data pipelines, data quality, and high-performance systems for processing large datasets. Their responsibilities include developing ETL processes, optimizing databases, and implementing data models to support research and trading strategies. Strong programming skills, expertise in big data technologies, and knowledge of quantitative methods are essential for this role.

What is the difference between Quantitative Data Engineer vs Data Scientist?

AspectQuantitative Data EngineerData Scientist
Primary FocusBuilding data pipelines, data infrastructure, and ensuring data qualityAnalyzing data, creating models, and deriving insights
Skills & ToolsSQL, Python, Spark, ETL processes, data architectureStatistics, machine learning, Python/R, data visualization
CredentialsComputer science, engineering, or related degrees; certifications in data engineeringStatistics, data science, or related degrees; certifications in data analysis or machine learning
Work EnvironmentData engineering teams, data infrastructure projectsData analysis teams, research, and modeling projects

While both roles work closely with data, Quantitative Data Engineers focus on building and maintaining data systems, whereas Data Scientists analyze data to generate insights and models. They often collaborate but have distinct skill sets and responsibilities within data-driven organizations.

How does a quantitative data engineer typically collaborate with data scientists and quantitative analysts on projects?

Quantitative Data Engineers work closely with data scientists and quantitative analysts to design, build, and optimize data pipelines that support complex modeling and analytics. They are often responsible for ensuring data quality, scalability, and efficient data processing, enabling analysts to focus on developing models and extracting insights. Regular collaboration includes translating analytical requirements into technical solutions, troubleshooting data issues, and iterating on data infrastructure to support evolving project needs. This teamwork fosters an environment where technical and analytical expertise complement each other, leading to more robust and actionable results.
What are popular job titles related to Quantitative Data Engineer jobs in California? For Quantitative Data Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Quantitative Data Engineer jobs in California look for? The top searched job categories for Quantitative Data Engineer jobs in California are:
What cities in California are hiring for Quantitative Data Engineer jobs? Cities in California with the most Quantitative Data Engineer job openings:
Quantitative Data Engineer jobs near you

Senior Data Engineer

Triumph

San Francisco, CA • On-site

$124K - $169K/yr

Full-time

Re-posted 5 hours ago

Job description

Job Summary:
Triumph is a skill-based real-money gaming platform in a period of rapid growth. As the first dedicated data engineering hire, you'll own the full data stack, including ingestion, transformation, and pipeline reliability, while collaborating with both quantitative strategy and engineering teams.
Responsibilities:
• Architect and own the data warehouse. Design and optimize our BigQuery environment for performance, cost, and reliability as data volumes scale with user growth.
• Build and maintain transformation layers. Own our dbt project end-to-end, including models, testing, documentation, and CI/CD, turning raw event streams into clean, trusted datasets.
• Pipeline orchestration. Build and manage robust data pipelines with proper orchestration, monitoring, alerting, and failure recovery. Nothing should break silently.
• Real-time data systems. Design and implement streaming infrastructure for use cases where batch processing falls short: live game economics, real-time risk signals, and in session player behavior.
• Reverse ETL and production integration. Close the loop between model outputs and the product by getting scores, segments, and predictions back into production systems where they drive real decisions.
• Data quality and reliability. Build the testing, validation, and monitoring frameworks that let a small team trust the data at scale.
• Partner with DS and engineering. You'll sit between two teams that move fast and need different things from the data layer. Translate between them and make both more productive.
Qualifications:
Required:
• Strong software engineering fundamentals. You write clean, maintainable, well-tested code.
• Deep experience with SQL and Python in production data contexts.
• Hands-on experience with data warehousing (BigQuery, Snowflake, Redshift, or similar) and transformation frameworks (dbt strongly preferred).
• Experience building and operating data pipelines with orchestration tooling (Airflow, Dagster, Prefect, or similar).
• Understanding of data modeling patterns (dimensional modeling, slowly changing dimensions, incremental materialization).
• Ability to work independently and make sound architectural decisions. You'll have a lot of autonomy and you need to use it well.
Preferred:
• Experience with streaming/real-time data systems (Kafka, Pub/Sub, Flink, or similar).
• Familiarity with analytics engineering and the modern data stack (Fivetran, Statsig, or similar tools).
• Exposure to quantitative or financial data environments where correctness and latency matter.
• Experience being an early or first data engineering hire. You've built from zero before and know what to prioritize.
Company:
Triumph is a game-developing software firm. Founded in 2020, the company is headquartered in San Francisco, USA, with a team of 51-200 employees. The company is currently Early Stage.

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