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Remote Hedge Fund Data Engineer Jobs in Missouri

Jobgether

$88K - $106K/yr

This is a remote opportunity for an experienced data engineer to play a key role in a large-scale digital transformation initiative. You will design, develop, and maintain scalable data solutions ...

Jobgether

$88K - $106K/yr

Install, configure, monitor, and troubleshoot Talend Remote Engine environments while maintaining ... Collaborate with data engineers, platform administrators, business stakeholders, and vendor support ...

All Generation Tech

Data Engineer-US

Columbia, MO · On-site +1

$109K - $130K/yr

We are seeking a Senior Data Engineer to design, implement, and maintain scalable data pipelines ... Columbia, MO (Hybrid - 1 week in office, 1 week remote) Experience: 4+ years Schedule: Full-time, ...

Koantek

Data Engineer - Multiple Positions

Chesterfield, MO · Remote

$113K - $136K/yr

United States - Remote Employment Type: Full-Time and Contract Data Engineer Description: As a Data Engineer at Koantek, you will leverage advanced data engineering techniques and analytics to ...

Kohl's

$112K - $148K/yr

Additional tasks may be assigned Addendum SENIOR BIG DATA SOFTWARE ENGINEER * Develop, automate, and maintain batch and streaming ETL pipelines using Apache Airflow, Apache Spark, Python, and Scala.

Jobgether

$81K - $111K/yr

As a Senior Data & Analytics Engineer, you'll take end-to-end ownership of a modern data platform and business intelligence layer within a fully remote, international environment. You'll help ...

Jobgether

$180K/yr

Our partner is looking for a Senior Software Engineer (Data) based in Netherlands. This is an ... Fully remote and distributed working environment with flexibility to structure work around personal ...

S2Tech

Manual Test Engineer (Remote)

Chesterfield, MO · On-site +1

The goal of the Fortune Fund is to close the rural/urban divide by ensuring children in rural ... Ability to coordinate test data needs with business, technical, and data conversion teams

Jobgether

$80K - $110K/yr

This fully remote role is ideal for an experienced engineer who enjoys solving foundational ... Develop scalable data and knowledge pipelines covering ingestion, embeddings, retrieval, vector ...

Jobgether

... engineering. You will help define standards that improve data discoverability, reliability, security, and usability for both people and AI systems. This remote contract role is suited to a highly ...

Yuno

Remote, Europe Full Time Experienced Engineering Manager +6 Years of Experience Who We Are At Yuno ... Our data platform is what makes that visible - to our product teams, our clients, and ourselves. As ...

Imperial PFS

Analytics Engineer I

Kansas City, MO · On-site +1

$111K - $134K/yr

Kansas City, MO (4 days in-office, 1 day remote) Experience Level: Mid-level (2-4 years) Department: Data Analytics Team About the Role An Analytics Engineer builds and maintains the foundational ...

Imperial PFS

Analytics Engineer I

Kansas City, MO · On-site +1

$111K - $134K/yr

Kansas City, MO (4 days in-office, 1 day remote) Experience Level: Mid-level (2-4 years) Department: Data Analytics Team About the Role An Analytics Engineer builds and maintains the foundational ...

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Remote Hedge Fund Data Engineer information

What does a remote hedge fund data engineer do?

A Remote Hedge Fund Data Engineer is responsible for designing, building, and maintaining data pipelines and infrastructure that support the data needs of a hedge fund, all while working from a remote location. They collect, process, and analyze large volumes of financial and market data to enable investment strategies and decision-making. This role often involves working with modern data technologies, ensuring data quality, and collaborating with portfolio managers, analysts, and other engineers. Remote Data Engineers must also ensure secure and efficient data flow, troubleshoot issues, and optimize data systems for performance.

What are the key skills and qualifications needed to thrive as a remote hedge fund data engineer?

To thrive as a Remote Hedge Fund Data Engineer, you need strong programming skills (typically in Python, SQL, or Java), a solid understanding of financial data structures, and a degree in computer science, engineering, or a related field. Expertise in cloud platforms (such as AWS or Azure), data pipeline tools (like Apache Spark or Airflow), and experience with big data technologies are commonly required, along with relevant certifications. Exceptional analytical thinking, attention to detail, and clear communication help you proactively solve complex problems and collaborate effectively with distributed teams. These skills are crucial for ensuring the timely, accurate, and secure processing of large-scale financial data that drives investment decisions.

How does a remote hedge fund data engineer typically collaborate with portfolio managers and quantitative analysts?

As a Remote Hedge Fund Data Engineer, you will frequently work alongside portfolio managers and quantitative analysts to ensure access to timely, high-quality data for investment decision-making. Collaboration often involves gathering requirements for new data sources, supporting the development and maintenance of data pipelines, and troubleshooting data quality issues. Effective communication is essential, as you'll need to translate business needs into technical solutions and provide ongoing support for data-driven strategies, all while working within a distributed team environment. Regular virtual meetings, shared documentation, and version control tools help maintain alignment and foster a collaborative workflow.

What is the difference between Remote Hedge Fund Data Engineer vs Remote Quantitative Analyst?

AspectRemote Hedge Fund Data EngineerRemote Quantitative Analyst
Required CredentialsBachelor's in Computer Science, Data Science, or related field; experience with data engineering toolsBachelor's or higher in Mathematics, Statistics, or related; programming skills in Python, R
Work EnvironmentFinancial firms, hedge funds, or asset management companies; focus on data pipelinesResearch firms, hedge funds, or investment banks; focus on modeling and analysis
Employer & Industry UsageCommonly employed in hedge funds for data infrastructureUsed for developing trading strategies and risk models in finance

The main difference is that Remote Hedge Fund Data Engineers focus on building and maintaining data systems, while Remote Quantitative Analysts develop models and strategies. Both roles require strong analytical skills, but their daily tasks and focus areas differ within the hedge fund industry.

What are popular job titles related to Remote Hedge Fund Data Engineer jobs in Missouri?

For Remote Hedge Fund Data Engineer jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Remote Hedge Fund Data Engineer jobs in Missouri look for?

The top searched job categories for Remote Hedge Fund Data Engineer jobs in Missouri are:

What cities in Missouri are hiring for Remote Hedge Fund Data Engineer jobs?

Cities in Missouri with the most Remote Hedge Fund Data Engineer job openings:

Remote Hedge Fund Data Engineer jobs near you

Data Engineer - Senior

Remote

Jobgether
See more jobs at Jobgetherexternal

$88K - $106K/yr

Contractor

This job post has expired 4 days ago. Applications are no longer accepted.

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer - Senior based in Netherlands.

This is a remote opportunity for an experienced data engineer to play a key role in a large-scale digital transformation initiative. You will design, develop, and maintain scalable data solutions that support reliable, analytics-ready information across the organization. Working closely with business stakeholders, product owners, architects, and technical teams, you will help turn diverse data sources into trusted and usable datasets. The role has a strong focus on the Microsoft Azure data ecosystem and modern cloud-based data architectures. You will work extensively with Azure Data Factory, Databricks, Synapse Analytics, Data Lake Storage Gen2, Python, SQL, and Delta Lake. This is an environment where strong engineering practices, problem-solving, and data quality directly contribute to business and technology outcomes.

Accountabilities
  • Design, develop, and maintain scalable, reliable data solutions supporting a large-scale digital transformation program.
  • Build and optimize robust ETL/ELT pipelines that integrate data from diverse sources into trusted, analytics-ready datasets.
  • Develop cloud-based data solutions using the Microsoft Azure ecosystem, including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure SQL, and related services.
  • Use Python and SQL to develop data transformations, processing workflows, integrations, and analytical data solutions.
  • Design and manage data models and architectures that support scalability, reliability, performance, and data quality.
  • Work extensively with Azure Databricks and Delta Lake to build and optimize modern data processing and storage solutions.
  • Collaborate with business stakeholders, product owners, data architects, and technical teams to understand requirements and translate them into effective data engineering solutions.
  • Apply version control and engineering best practices using tools such as Git to support maintainable, collaborative development.
  • Leverage AI-powered tools where appropriate for code generation, data analysis, automation, optimization, and other data engineering activities.
  • Troubleshoot technical issues, optimize data workflows, and continuously improve pipeline performance, reliability, and maintainability.
  • Communicate technical concepts clearly and contribute to effective collaboration across business and technical teams.
Requirements:
  • At least 5 years of hands-on experience with Python and SQL in a data engineering environment.
  • At least 3 years of experience working with Azure services, including Azure Storage, Azure SQL, Azure Synapse, and Azure networking.
  • At least 3 years of hands-on experience with Azure Databricks and Delta Lake.
  • At least 3 years of experience designing data solutions and developing trusted, analytics-ready datasets.
  • At least 4 years of experience with version control systems, particularly Git.
  • At least 1 year of practical experience using AI tools for code generation, data analysis, automation, optimization, or related data engineering tasks.
  • Strong understanding of data engineering principles, ETL/ELT processes, data integration, and data pipeline development.
  • Advanced SQL development and data transformation capabilities.
  • Proven experience working with cloud-based data platforms and modern data architectures.
  • Strong analytical and problem-solving abilities, with a structured approach to diagnosing and resolving complex technical challenges.
  • Excellent communication and collaboration skills, with the ability to work effectively with both technical teams and business stakeholders.
  • Ability to work independently in a remote environment while maintaining strong ownership, organization, and delivery focus.
Benefits:
  • Fully remote position, offering flexibility to work from Slovenia.
  • Opportunity to contribute to a large-scale digital transformation initiative with significant data engineering scope.
  • Work with a modern Microsoft Azure cloud data ecosystem and widely used data engineering technologies.
  • Exposure to advanced platforms and tools including Azure Databricks, Delta Lake, Azure Synapse, Azure Data Factory, Python, and SQL.
  • Opportunity to apply AI-powered engineering tools to improve development, automation, analysis, and optimization.
  • Collaboration with multidisciplinary teams including business stakeholders, product owners, data architects, and technical specialists.
  • Opportunity to work on scalable, production-focused data solutions with direct business impact.
  • Remote working environment designed to support autonomy and flexibility.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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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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