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Quantitative Data Engineer Jobs in Colorado (NOW HIRING)

Lead Data Engineer

Englewood, CO · On-site

$101K - $133K/yr

Job Summary (Lead Data Engineer - Englewood, CO) - Lead the design, development, and maintenance of ... Bachelor's (8+ years) or Master's (6+ years) in computer science or related quantitative field ...

Required : • Bachelor's Degree in Computer Science, Data Science, Software Engineering, or a related quantitative field • 7+ Years in Data Engineering • 2+ years in a Lead or Staff capacity ...

Bachelor's Degree in Computer Science, Data Science, Software Engineering, or a related quantitative field. Master's Degree in a technical field preferred. * 7+ Years in Data Engineering: With at ...

Own the multi-asset data layer: market data, macro, fundamentals, fund and index data, internal ... Write production code that other quants want to build on. Own reliability, testing, and ...

... quantitative urban planner, and who brings the technical skills to build and operate the data infrastructure their own work requires. This is not primarily an engineering role, though the ideal ...

... quantitative urban planner, and who brings the technical skills to build and operate the data infrastructure their own work requires. This is not primarily an engineering role, though the ideal ...

... quantitative urban planner, and who brings the technical skills to build and operate the data infrastructure their own work requires. This is not primarily an engineering role, though the ideal ...

... quantitative urban planner, and who brings the technical skills to build and operate the data infrastructure their own work requires. This is not primarily an engineering role, though the ideal ...

Principal Systems Engineer

Longmont, CO · On-site

$100K - $178K/yr

S., Attalon engineers critical optical, laser, and coating technologies that enable systems to see ... quantitative data analysis. This role involves leading projects, collaborating with ...

Apply Early

Translate business concepts into clear requirements and user stories for design and engineering ... Strong analytical mindset with the ability to interpret both qualitative and quantitative data.

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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 Colorado? For Quantitative Data Engineer jobs in Colorado, the most frequently searched job titles are:

Lead Data Engineer

eFulgent

Englewood, CO • On-site

$101K - $133K/yr

Contractor

Posted 5 days ago


Job description

Job Summary (Lead Data Engineer - Englewood, CO)
- Lead the design, development, and maintenance of scalable ETL pipelines using Spark to ensure data quality and availability.
- Execute advanced analytics, machine learning, and generative AI techniques to enhance network security and operational efficiency.
- Leverage AWS for building and deploying scalable data engineering solutions.
- Implement monitoring, alerting, and continuous integration/delivery pipelines for reliable data operations.
- Develop and manage data integration solutions to support analytics/reporting needs.
- Conduct complete analytics lifecycle: data exploration, grooming, modeling, validation, and prototyping.
- Analyze diverse data sources (APIs, flat files, databases, distributed file systems) for analytic relevance.
- Interpret and communicate analytic results to drive organizational action and improvements.
- Collaborate with cross-functional teams to integrate analytic solutions into production and educate stakeholders.
- Mentor peers and share expertise in analytic techniques, tools, and best practices.
- Required skills: ETL, ML Ops, AI/ML, Data Warehousing, Spark, Python, Scala/Java, SQL, Big Data tools, statistical analysis.
- Good to have: AWS, Linux, text analysis/mining, NoSQL databases.
- Education/Experience: Bachelor’s (8+ years) or Master’s (6+ years) in computer science or related quantitative field.
- Work location: Onsite in Englewood, CO; 12-month contract; visa-independent candidates only.