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Remote Hedge Fund Data Engineer Jobs in Minnesota

Power BI Data Engineer

Minneapolis, MN · On-site +1

$119K - $143K/yr

This position is remote with preference to align to one of Legence' s office locations. Key ... PL-300 (Power BI Data Analyst), DP-203 (Data Engineer), or DP-500 (Enterprise Data Analyst)

Power BI Data Engineer

Minneapolis, MN · On-site +1

$119K - $143K/yr

This position is remote with preference to align to one of Legence' s office locations. Key ... PL-300 (Power BI Data Analyst), DP-203 (Data Engineer), or DP-500 (Enterprise Data Analyst)

Power BI Data Engineer

Minneapolis, MN · On-site +1

$119K - $143K/yr

This position is remote with preference to align to one of Legence' s office locations. Key ... PL-300 (Power BI Data Analyst), DP-203 (Data Engineer), or DP-500 (Enterprise Data Analyst)

AI Resilience Fund Manager

Minneapolis, MN · Remote

$72K - $98K/yr

Location: Remote (U.S. or Canada) Type: US Applicants - Full-Time; Canadian Applicants ... Across strategy, engineering, design, data, and operations, we seek out teammates who raise the bar ...

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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 the most commonly searched types of Hedge Fund Data Engineer jobs in Minnesota?

The most popular types of Hedge Fund Data Engineer jobs in Minnesota are:

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

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

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

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

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

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

Infographic showing various Remote Hedge Fund Data Engineer job openings in Minnesota as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Senior Cloud Data Engineer - Remote

UnitedHealth Group

Eden Prairie, MN • Remote

$108K - $146K/yr

Full-time

Retirement

Posted 11 days ago


UnitedHealth Group rating

7.6

Company rating: 7.6 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

189th of 893 rated healthcare providers


Job description

OptumInsightis improving the flow of health data and information to create a more connected system. We remove friction and drive alignment between care providers and payers, andultimately consumers. Our deepexpertisein the industry and innovative technology empower us to help organizations reduce costs while improving risk management,qualityand revenue growth. Ready to help us deliver results that improve lives?Join us to startCaring. Connecting. Growing together.  

The Senior Cloud Data Engineer - Remote will be a key technical resource during the solution implementation of cloud-centric data management architecture. The primary role of the Senior Cloud Data Engineer is to take the design and technical specifications and develop effective and high-quality technical solutions that meet business requirements. The technical domain of the Cloud Data Engineer includes understanding Data Acquisition/Integration (DA/DI) best practices, tools and technologies, security in the environment, understanding of different data warehousing and dimensional modelling concepts, DI development, performance tuning and support system testing.

We are seeking an experienced Senior Cloud Data Engineer to support large-scale Cloud Data Modernization initiatives. The successful candidate will lead the migration and modernization of legacy data platforms, ETL/ELT processes, and enterprise data warehouses to cloud-native solutions leveraging Azure, Snowflake, Databricks, and modern data engineering practices.  This role combines hands-on engineering, technical leadership, and solution implementation responsibilities to deliver scalable, secure, high-quality cloud data platforms that support analytics, reporting, and operational workloads.

You'll enjoy the flexibility to work remotely* from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Primary Responsibilities:
Cloud Data Modernization

  • Provide technical leadership in design and engineering for the modernization of legacy data platforms, ETL/ELT processes, and enterprise data warehouses to new technologies in the Public Cloud (AWS/Azure)
  • Review and analyze existing SSIS, SQL Server, and legacy ETL implementations and develop modernization strategies
  • Design, develop, and implement cloud-native data solutions utilizing Azure Data Factory (ADF), Azure Data Lake Storage Gen2 (ADLS Gen2), Snowflake, Databricks, Azure cloud services

Data Engineering & Integration

  • Design and develop scalable ETL/ELT pipelines supporting batch and streaming workloads
  • Create source-to-target mappings and implement data ingestion frameworks supporting structured and unstructured data
  • Build and optimize cloud data warehouses, data marts, and lakehouse architectures
  • Implement full and incremental load patterns, change data capture (CDC), and automated data validation processes
  • Perform data profiling, data quality assessment, and root cause analysis for data issues
  • Create Process Flows using diagraming tools like Visio
  • Automate pipeline processes using scheduling tools like AirFlow
  • Conduct ETL/ELT unit testing; participate in system and integration testing; identify and remedy solution defects

Data Architecture & Modeling

  • Design and implement enterprise data warehouse solutions utilizing dimensional modeling concepts including Star schemas, Snowflake schemas, Fact and dimension design, Data pipeline architectures
  • Collaborate with business and technical stakeholders to understand requirements and translate them into scalable solutions

Cloud Security & Governance

  • Implement appropriate data security, privacy, governance, and compliance controls
  • Ensure compliance with organizational standards for data protection, auditability, and data quality
  • Proven expertise in managing highly sensitive PHI/PII, claims, provider, clinical, and member data while supporting Risk Adjustment (HCC/RAF), quality measurement programs, and ensuring HIPAA compliance, data governance, privacy, and security standards
  • Establish data lineage, monitoring, and operational support processes
  • Architected HIPAA-compliant Azure and Snowflake-based healthcare analytics platforms integrating Claims, Membership, Provider, Clinical, Laboratory, Pharmacy, and Care Management data

DevOps & Delivery

  • Implement CI/CD pipelines and DevOps practices using GitHub Actions and other modern delivery tools
  • Support Agile software delivery practices and contribute across the full development lifecycle, including: Requirements, Design, Development, Testing, Deployment, Production support

Solution Architecture

  • Lead the assessment of current-state data platforms and develop future-state cloud data architecture roadmaps aligned with business objectives and enterprise technology strategy
  • Define and document solution architecture patterns, integration approaches, data flows, and technical design specifications for enterprise-scale modernization initiatives
  • Create implementation roadmaps, effort estimates, technical dependencies, and migration strategies for large-scale cloud transformation programs

Leadership & Collaboration

  • Provide technical leadership for cloud data engineering initiatives
  • Mentor junior engineers and contribute to engineering best practices
  • Collaborate effectively in matrixed environments with business stakeholders, architects, analysts, developers, and project teams
  • Proactively identify implementation risks, constraints, and improvement opportunities
  • Self-driven, ownership mindset to navigate ambiguity, identify options to resolve constraints, mitigate implementation risks and define solutions to implementation challenges with minimal supervision
  • Build partnership and rapport with client technical resources by demonstrating strong written and verbal communication, presentation, analytical and interpersonal skills
  • Ability to work closely with Business Analysts and SMEs to understand business requirements
  • Ability to work in a matrixed team environment with distributed responsibility across different teams
  • Proactive and diligent in identifying and communicating scope, design, development issues and recommending potential solutions

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications:

  • 5 years of experience in designing, developing, and implementing enterprise data warehouse and analytics solutions on prem and on cloud
  • 3 years of hands-on cloud data engineering experience utilizing Azure cloud technologies
  • 3 years of experience working as part of data engineering teams, including offshore teams, through a product life cycle - requirements, design, development, testing and deployment
  • Experience with Azure Data Factory (ADF), Databricks, Snowflake, ADLS Gen2, Synapse Analytics, Azure SQL Database, Microsoft Fabric, SQL Server, Python, Spark/Pyspark, ETL/ELT development
  • Hands-on experience with Azure cloud platform administration, including performance tuning and workload management
  • Understanding of enterprise data warehousing concepts, dimensional modeling, Star and Snowflake schema design, data quality management, data governance, metadata-driven frameworks, data lineage, source-to-target mapping, and scalable cloud data pipeline architectures
  • Experience designing and implementing healthcare data and analytics solutions, including healthcare claims data, payment integrity, cloud data modernization, data warehouse migration, and platform transformation initiatives
  • Experience implementing CI/CD and DevOps practices using GitHub, GitHub Actions, Azure DevOps, and automated deployment frameworks
  • Experience working within Agile delivery methodologies
  • Hands-on experience with AI-enabled data engineering tools
  • Partner with AI Engineering on RAG pipelines, embedding strategies, and vector stores that ground responses in EHR data, clinical documentation, and medical literature, including data refresh patterns synchronized with EHR updates and evidence-based guideline revisions
  • Ability to travel 10 - 20% when required

Preferred Qualifications:

  • Azure Administrator, Snowflake, Azure, Databricks, or Cloud Data Engineering certifications
  • Experience with cloud data platforms across Azure, AWS, and/or Google Cloud
  • Experience working with healthcare claims, member, enrollment, or clinical data
  • Experience with Infrastructure as Code (Terraform) and container technologies (Docker, Kubernetes)
  • Demonstrated ability to meet tight deadlines, follow development standards and effectively raise critical issues with the client
  • Excellent analytical, problem-solving, communication, and stakeholder management skills
  • Demonstrated ability to work independently, manage ambiguity, and deliver high-quality solutions

*All employees working remotely will berequiredto adhere to UnitedHealth Group's Telecommuter Policy

Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $91,700 to $163,700 annually based on full-time employment. We comply with all minimum wage laws as applicable.

Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age,locationand income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalizedgroupsand those with lower incomes. We are committed to mitigating our impact on the environment and enabling and deliveringequitablecare that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.

UnitedHealth Group is adrug -free workplace. Candidatesare required topass a drug test before beginning employment.


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