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Senior Hedge Fund Data Engineer Jobs in Indiana (NOW HIRING)

Sr Databricks Data Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

As a Databricks Engineer in our AI & Data practice, you will design, build, and optimize cloud-based data engineering solutions that support large-scale transformation. You will work with business ...

Senior Data Engineer (in person)

Westfield, IN · On-site

$101K - $138K/yr

At SEP, we're building that foundation - and we're looking for a Senior Data Engineer who's ready to lead the way. We've been partnering with companies to build software that matters since 1988. From ...

At SEP, we're building that foundation - and we're looking for a Senior Data Engineer who's ready to lead the way. We've been partnering with companies to build software that matters since 1988. From ...

Senior Data Engineer (in person)

Westfield, IN · On-site

$101K - $138K/yr

At SEP, we're building that foundation -- and we're looking for a Senior Data Engineer who's ready to lead the way. We've been partnering with companies to build software that matters since 1988.

ETL/Data Engineer

Indianapolis, IN · On-site

$107K - $129K/yr

Vergence is seeking a Senior Azure Data Engineer to help design, build, and operate our next-generation enterprise data platform on Microsoft Azure. You will own end-to-end delivery of data pipelines ...

Showing results 21-40

Senior Hedge Fund Data Engineer information

What does a senior hedge fund data engineer do?

A Senior Hedge Fund Data Engineer designs, builds, and manages data infrastructure that supports the investment strategies of a hedge fund. They work with large, complex financial datasets, ensuring data quality, accessibility, and security for analysts and portfolio managers. Their responsibilities often include developing data pipelines, integrating market data feeds, optimizing database performance, and collaborating with quantitative researchers and traders to meet evolving business needs.

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

To thrive as a Senior Hedge Fund Data Engineer, you need advanced skills in data engineering, programming (commonly Python or Java), quantitative analysis, and a relevant degree in computer science, mathematics, or a related field. Experience with big data platforms (such as Spark or Hadoop), cloud services (AWS, Azure), database systems (SQL/NoSQL), and knowledge of financial data feeds or APIs is typically required. Strong problem-solving, communication, and collaboration skills help you translate complex business needs into robust technical solutions. These skills ensure accurate, scalable data infrastructure that supports timely and effective investment decision-making in a high-stakes environment.

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

A Senior Hedge Fund Data Engineer works closely with portfolio managers and analysts to understand their data needs and translate them into robust data pipelines and analytical tools. This collaboration often involves gathering requirements for new data sources, ensuring data quality and reliability, and building custom solutions that enable faster and more accurate investment decisions. Effective communication and the ability to quickly iterate on feedback are essential, as the business needs can change rapidly in the hedge fund environment. Additionally, Senior Data Engineers may mentor junior team members and coordinate with IT for infrastructure and security compliance.

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

AspectSenior Hedge Fund Data EngineerHedge Fund Data Analyst
CredentialsBachelor's/Master's in Computer Science, Data Science, or related field; experience with data engineering toolsBachelor's in Finance, Economics, or related; strong analytical skills
Work EnvironmentDesigning data pipelines, managing large datasets, working with engineering teamsAnalyzing data, generating reports, supporting investment decisions
Industry UsageUsed in hedge funds for data infrastructure and managementUsed for performance analysis and reporting within hedge funds

The Senior Hedge Fund Data Engineer focuses on building and maintaining data infrastructure, while the Hedge Fund Data Analyst interprets data to support investment strategies. Both roles are essential in hedge fund operations but differ in technical depth and focus.

What are the most commonly searched types of Hedge Fund Data Engineer jobs in Indiana?

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

What are popular job titles related to Senior Hedge Fund Data Engineer jobs in Indiana?

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

What job categories do people searching Senior Hedge Fund Data Engineer jobs in Indiana look for?

The top searched job categories for Senior Hedge Fund Data Engineer jobs in Indiana are:

What cities in Indiana are hiring for Senior Hedge Fund Data Engineer jobs?

Cities in Indiana with the most Senior Hedge Fund Data Engineer job openings:

$113K - $135K/yr

Full-time

Re-posted 12 hours ago


Job description

As an employee-owned company, DMA prioritizes employees. Low turnover rates and tenured teams are living proof:
  • 2025 Great Places to Work Certified
  • Employee stock ownership program eligibility begins on day one of employment (ESOP contribution is targeted at 6% of your annual compensation)
  • Company paid parental leave
  • Generous time off package
  • Multiple benefit plans, eligibility begins on day one of employment
  • Culturally focused on work/life balance, and the overall wellness of our employees

This is a hybrid position with an expectation to be in our Fort Wayne, IN office a minimum of two days per week. This position does not qualify for relocation assistance. Must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future. This position does not qualify for employment-based sponsorship.
Position Summary
The Data Analyst will be primarily responsible for creating and maintaining DMA's infrastructure and systems that enable the collection, storage, and processing of data. This role is essential for ensuring data is accessible, reliable, and optimized for analysis and decision-making.
Essential Duties and Responsibilities
• Design, build, and maintain robust data pipelines and ETL processes to ingest, transform, and deliver data from various sources.
• Mine data from primary and secondary sources, then reorganize said data in a format that can be easily read by either human or machine
• Use statistical tools to interpret data sets, pay particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts
• Collaborate with programmers and engineers to improve efficiency and data organization; improve performance through data structure and query optimization
• Ensure data integrity, quality, and security across all systems and platforms
• Work with departments to provide insight and identify opportunities, improvements, recommend system modifications, and develop policies for data governance
• Integrate structured and unstructured data from internal and external sources.
• Monitor and troubleshoot data workflows, resolving issues proactively
• Design, implement, and maintain critical data systems from ETL/ELT, Data Warehouse, BI Tools, and everything in between
• Maintain documentation for data architecture, processes, and standards
• Collaborate with data scientists, analysts, and product teams to support data needs.
• Analyze requirements from the business and provide solutions or guidance for solutions
• Work with senior data analyst to establish data governance
Non-Essential Duties and Responsibilities
• Perform other duties as assigned
Education and Qualifications
• Bachelor's degree in computer science, information systems, engineering, or related field.
• 2 to 5 years' experience as a data engineering role
• Familiarity with professional programming preferred
• Familiarity with relevant business domains
• Ability to analyze large datasets and write comprehensive reports
• Experience in data models and reporting packages
• Experience working with data and data analytics development, preferably within the Microsoft data platform
• Ability to understand business needs and translate them into technical solutions
• Works effectively with analysts, stakeholders, and IT teams to deliver data solutions that drive business value
• Proficiency in SQL and experience with relational and non-relational databases
• Proficient with ELT/ETL and Data Warehousing development
• Knowledge of relational databases and object-relational mapping concepts
• Commitment to data quality, governance, and compliance
• Understanding of data modeling, normalization, and schema design
• Excellent organizational skills: ability to handle multiple projects
• An analytical mind and inclination for problem-solving
• Strong verbal and written communication skills
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The Company is an equal employment opportunity employer and is committed to providing equal employment opportunities to its applicants and employees. The Company does not discriminate in employment opportunities or practices on the basis of race, color, religion, gender, national origin, citizenship, age, disability, veteran status, genetic information, or any other category covered by applicable federal, state, or local law. This equal employment opportunity policy applies to all employment policies, procedures, and practices, including but not limited to hiring, promotion, compensation, training, benefits, work assignments, discipline, termination, and all other terms and conditions of employment.
It is DMA's policy to make reasonable accommodations for qualified individuals with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please contact our Human Resources team at HRDepartment@dmainc.com or 800-309-2110 and choosing selection 6.