Data Operations Associate

POSITION SUMMARY  

Tiverton is seeking a Data Operations Associate to support our investment process and portfolio operations through data engineering analytics and AI-powered automation. This hybrid role combines data infrastructure development with investment analytics working across deal sourcing due diligence portfolio monitoring and LP reporting. The ideal candidate is a technically proficient generalist who enjoys building solutions across the full data stack - from pipeline engineering to business intelligence - and is excited to apply AI/ML tools to solve real-world problems in agricultural private equity. This role offers broad exposure to both the investment side (deal flow due diligence and fund analytics) and operations side (portfolio company data reporting automation and other analytics.  

The successful candidate will be self-motivated and energized by working with a group of thoughtful smart and skilled colleagues. He or she will enjoy being a part of a young hungry and collaborative organization focused on becoming the pre-eminent investment firm in US agriculture. 

 PRIMARY RESPONSIBILITIES 

• Data Infrastructure & Pipeline Engineering (40%) 
  • Build and maintain ETL pipelines pulling data from internal and external sources into our Snowflake data warehouse 
  • Develop Python and SQL automation scripts for recurring data processes 
  • Manage Snowflake data warehouse - schema design query optimization and data modeling 
  • Build API integrations for third-party data sources (pricing data B2B data providers market intelligence) 
  • Implement data quality checks validation rules and monitoring to ensure pipeline reliability 
  • Create web scraping solutions for data collection from public sources 
  • Maintain code repositories with proper version control and documentation 
• Investment Analytics & Deal Support (30%) 
  • Support deal pipeline analytics and sourcing workflows in our CRM 
  • Build models and analytics for sector trends (crop prices land values farm credit metrics) 
  • Extract and analyze data from appraisal documents financial statements and industry reports 
  • Develop due diligence analytical frameworks and data rooms for new investments 
  • Create LP reporting dashboards and automated quarterly reporting processes 
  • Support investment team with ad-hoc analytical requests and data visualization 
• AI/ML Implementation & Automation (20%) 
  • Leverage LLMs (OpenAI Claude) to accelerate document analysis data extraction and research workflows 
  • Build AI-powered automation for deal screening document processing and data enrichment 
  • Implement intelligent solutions for pattern recognition anomaly detection and data quality 
  • Use prompt engineering and AI coding assistants to rapidly prototype analytical tools 
  • Develop RAG (Retrieval-Augmented Generation) systems for knowledge management 
• Portfolio Company Support & Reporting (10%) 
  • Support portfolio company reporting requirements and data requests 
  • Build dashboards and reporting tools for portfolio operations teams 
  • Troubleshoot data issues and provide technical support to portfolio companies 
  • Partner with investment team to ensure clean reliable data for portfolio monitoring 

Qualifications :

REQUIRED 

• Technical Skills 
  • Strong proficiency in Python (pandas requests sqlalchemy) and SQL for data analysis and automation 
  • Experience with data pipelines ETL processes/tools (Fivetran etc) or data engineering workflows 
  • Working knowledge of cloud data warehouses (Snowflake Databricks BigQuery Redshift) 
  • Proficiency in business intelligence tools (Power BI Tableau Sigma or Looker) 
  • Advanced Excel skills including complex formulas pivot tables and data modeling 
  • Experience with API integrations and web scraping (REST APIs Beautiful Soup or similar) 
  • Comfortable with AI/ML tools: LangChain OpenAI API Claude API or similar frameworks 
  • Git version control and collaborative development workflows 

• Business & Analytical Skills 
  • Ability to translate business problems into technical solutions 
  • Strong problem-solving skills - can debug data issues independently 
  • Understanding of financial concepts and private equity metrics helpful but not required 
  • Strong communication skills - can explain technical concepts to non-technical stakeholders 
  • Self-directed with ability to prioritize and manage multiple projects 
  • Detail-oriented with focus on data quality and reliability 

• Experience & Background 
  • 1-3 years of experience in data engineering analytics data science or related technical roles 
  • Bachelors degree in Computer Science Data Science Engineering Finance or related field 
  • Internship or project experience with data pipelines analytics or automation acceptable 

PREFERRED/NICE TO HAVE 

• Experience building LLM-powered applications or automation tools 
• Familiarity with CRM systems (Affinity Salesforce) or investment workflow tools 
• Experience with document processing and unstructured data extraction 
• Knowledge of ML libraries (scikit-learn numpy) and model deployment 
• Exposure to private equity venture capital or investment banking 
• Understanding of DevOps practices - testing monitoring CI/CD 
• Knowledge of agricultural markets farm credit systems or commodity data 

Additional Information :

• Please submit examples of ETL/Data pipeline-related technical projects (GitHub repos portfolio sites or project descriptions welcome) 
• Competitive compensation package with eligibility for an annual bonus based on individual and Company performance  
• Generous PTO and paid holiday policy 
• Employee benefits package including Healthcare Dental Vision Group Life Insurance and 401(k)  
• Location: Raleigh North Carolina 

Remote Work :

No

Employment Type :

Full-time