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Remote Hedge Fund Data Engineer Jobs in Decatur, GA

Data Engineer - GCP

Atlanta, GA · On-site +1

$110K - $132K/yr

Our Google Cloud Data Engineer will play a key role in designing, developing, and managing scalable ... Flexible work environment and remote work options. Join us and be part of a team building ...

Data Engineer - GCP

Atlanta, GA · On-site +1

$110K - $132K/yr

Our Google Cloud Data Engineer will play a key role in designing, developing, and managing scalable ... Flexible work environment and remote work options. Join us and be part of a team building ...

Data Engineer - GCP

Atlanta, GA · Remote

$117K - $140K/yr

Our Google Cloud Data Engineer will play a key role in designing, developing, and managing scalable ... Flexible work environment and remote work options. Join us and be part of a team building ...

Data Engineer

Atlanta, GA · On-site +1

$110K - $132K/yr

The Data Engineer role is responsible for designing, building, and maintaining scalable data ... This opportunity is remote with the ideal candidate being located in DFW, Phoenix, Atlanta or ...

Remote-Data Engineer- Only W2

Atlanta, GA · Remote

$110K - $132K/yr

Data Engineer Location: Remote Role Focus: Pipeline Development + Support Key Skills / Responsibilities: Build and maintain ETL pipelines Support batch + CDC ingestion (including mainframe) Data ...

Senior Data Engineer

Alpharetta, GA · Remote

$103K - $140K/yr

... PA, Remote-RI, Remote-VA, St. Louis, Missouri Details Kemper is one of the nation's leading ... Provide technical leadership to data engineers, setting standards for solution design, coding ...

AWS Data Engineer

Atlanta, GA · Remote

$112K - $134K/yr

Perform data cleansing, data validation etc \n \n \n 3. Hands on ETL developer who is good at ... Toronto ON, Atlanta GA and Remote.\n \n \n \n \n \n

Data Architect (Remote)

Atlanta, GA · On-site +1

$61.25 - $78.75/hr

Data Architect 1 - US Remote About Axiom: As the leading alternative legal services provider ... The Data Architect directly manages the Data Engineer and operates in close coordination with the ...

Data Quality Engineer

Alpharetta, GA · Remote

$111K - $134K/yr

... Remote-OH, Remote-PA, Remote-RI, Remote-VA Details Kemper is one of the nation's leading ... Kemper is seeking a Data Quality Engineer specializing in Data Testing and Quality Engineering to ...

See us at Position Summary As a Lead Systems Engineer - Data at Bravo17, you will elevate data ... Remote; however we are looking to grow our presence in Atlanta, Chicago, Denver, and Washington DC ...

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Remote Hedge Fund Data Engineer information

See Decatur, GA salary details

$43.4K

$126.6K

$173.3K

How much do remote hedge fund data engineer jobs pay per year?

As of Jul 30, 2026, the average yearly pay for remote hedge fund data engineer in Decatur, GA is $126,646.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,800.00 and $134,200.00 per year, depending on experience, location, and employer.

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 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, and why are they important?

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 are popular job titles related to Remote Hedge Fund Data Engineer jobs in Decatur, GA? For Remote Hedge Fund Data Engineer jobs in Decatur, GA, the most frequently searched job titles are:
What job categories do people searching Remote Hedge Fund Data Engineer jobs in Decatur, GA look for? The top searched job categories for Remote Hedge Fund Data Engineer jobs in Decatur, GA are:
What cities near Decatur, GA are hiring for Remote Hedge Fund Data Engineer jobs? Cities near Decatur, GA with the most Remote Hedge Fund Data Engineer job openings:

Data Engineer - GCP

The Data Sherpas

Atlanta, GA • On-site, Remote

$110K - $132K/yr

Full-time

Medical, Dental, Vision

Re-posted 20 days ago


Job description

Who We Are: 

We are a dynamic team focused on building innovative and scalable data solutions on Google Cloud Platform (GCP). Our Google Cloud Data Engineer will play a key role in designing, developing, and managing scalable data pipelines and data infrastructure, ensuring data availability, accuracy, and performance for business insights and machine learning models.


What We Are Looking For: 

We are seeking an experienced and highly skilled Google Cloud Data Engineer who will be responsible for developing and managing data pipelines on GCP. The ideal candidate will bring strong expertise in cloud-based data processing, big data technologies, and data modeling to help us provide high-performance data solutions.


Responsibilities:

Data Pipeline Development and Management:

  • Design, build, and maintain scalable and reliable data pipelines using Cloud Dataflow, Cloud Pub/Sub, and Cloud Composer.
  • Develop ETL/ELT processes to process and transform large volumes of structured and unstructured data.
  • Optimize data pipeline performance, scalability, and reliability.
  • Ensure data processing and ingestion workflows are monitored and meet performance SLAs.

Data Storage and Management:

  • Design and implement data storage solutions using BigQuery, Cloud Storage, and Firestore.
  • Optimize data structures and partitioning for performance and cost efficiency.
  • Ensure data security, integrity, and availability in all storage solutions.
  • Manage data lifecycle policies and archiving processes.

Data Transformation and Processing:

  • Develop data transformation processes using BigQuery, Apache Beam, and Cloud Functions.
  • Implement data quality checks, validation rules, and monitoring solutions.
  • Support real-time and batch data processing needs.

Data Integration and Automation:

  • Integrate data from multiple sources, including APIs, databases, and third-party applications.
  • Automate data ingestion, transformation, and export using tools like Cloud Composer and Cloud Functions.
  • Ensure data consistency across different environments and systems.

Collaboration and Stakeholder Engagement:

  • Work closely with data scientists and analysts to understand data needs and business goals.
  • Provide technical guidance and best practices to the data engineering and business teams.
  • Collaborate with security and compliance teams to ensure data governance standards are met.

Performance Monitoring and Troubleshooting:

  • Monitor data pipeline performance and troubleshoot issues in real-time.
  • Analyze data pipeline failures and implement fixes to prevent recurrence.
  • Set up logging and monitoring using Stackdriver and Cloud Monitoring.


Qualifications:

  • Bachelor’s degree in Computer Science, Data Engineering, or a related field; Master’s degree is a plus.
  • 3+ years of experience in data engineering, with at least 2+ years working with Google Cloud Platform.
  • Google Professional Data Engineer certification is required.
  • Strong proficiency with GCP services such as BigQuery, Cloud Dataflow, Cloud Composer, Cloud Pub/Sub, Firestore, and Cloud Functions.
  • Hands-on experience with big data tools and frameworks such as Apache Beam, Hadoop, Spark, or Flink.
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Strong knowledge of SQL, data modeling, and query optimization.
  • Experience with CI/CD tools and version control (e.g., Git, Cloud Build).
  • Strong understanding of data governance, security, and compliance requirements.
  • Ability to manage large-scale data processing and real-time data pipelines.
  • Excellent problem-solving, analytical, and communication skills.


Preferred Skills:

  • Experience with machine learning pipelines and AI/ML model deployment.
  • Familiarity with Terraform and Infrastructure as Code (IaC) principles.
  • Experience with NoSQL databases and key-value stores on GCP.
  • Knowledge of containerization and orchestration using Google Kubernetes Engine (GKE).


What We Offer:

  • Competitive salary and performance-based incentives.
  • Comprehensive health, dental, and vision coverage.
  • Professional development and training opportunities (including GCP certification).
  • Flexible work environment and remote work options.


Join us and be part of a team building innovative and scalable data solutions on Google Cloud Platform!


This position is open to multiple engagement models, including Permanent/Full-Time, Contract, or Corp-to-Corp (C2C) arrangements. We are looking for the best talent and are flexible on the employment structure for the right candidate.


We cannot work with third-party agencies at this time. Resumes submitted via unapproved agencies will be automatically rejected.