AI Engineer Trading Analytics & Data Engineering

Qualifications

• The ideal candidate combines technical depth with strong communication skills and the ability to translate ambiguous business questions into scalable, production ready solutions

• Hands on experience with Databricks and Apache Spark (PySpark, SQL, Delta Lake, Unity Catalog)

• Familiarity with modern engineering practices and tooling, such as CI/CD pipelines, infrastructure as code, experimentation frameworks, and data governance

• Strong communication and collaboration skills, with the ability to work effectively with technical and non technical stakeholders

• 1 more items(s)

Responsibilities

• This role partners closely with traders and trading analysts to design and deliver AI powered analytical solutions using large scale market and fundamentals data

• Hybrid work model with close collaboration alongside trading and analytics teams

• Fast paced, iterative development approach-prototype quickly, refine with user feedback, and harden solutions for production

• Strong focus on operational excellence, including secure CI/CD practices, automated testing, and production reliability

• Design, develop, and deliver AI driven analytics for front office use cases, including seasonality analysis, correlation, regression, forecasting, and scenario modeling

• Build and maintain scalable, reusable data pipelines using Databricks and Spark (PySpark, SQL, Delta Lake, Unity Catalog)

• Perform statistical and econometric analyses on large, complex datasets such as market pricing and fundamental time series data

• Collaborate directly with business stakeholders to gather requirements, clarify objectives, and communicate insights effectively

• Develop and integrate LLM based and agentic workflows, including prompt engineering, orchestration, retrieval, and guardrails

• Productionize solutions with appropriate testing, observability, documentation, and version control

• Strong data engineering experience, including data ingestion, modeling, orchestration, and performance optimization

• Solid foundation in statistics, economics, or data science, particularly related to time series analysis

• Experience implementing LLM based solutions, including prompt design, retrieval workflows, and agent frameworks

• 10 more items(s)

More job highlights

Job description

Dice is the leading career destination for tech experts at every stage of their careers.

Our client, Aroha Technologies, is seeking the following.

Apply via Dice today!

Job Title: AI Engineer Trading Analytics & Data Engineering

Location: Houston, TX (Hybrid)

Employment Type: Contract (7 months, with potential extension)

About The Role

We are seeking an AI Engineer with a strong foundation in... data engineering and applied analytics to support trading and market analytics use cases.

This role partners closely with traders and trading analysts to design and deliver AI powered analytical solutions using large scale market and fundamentals data.

The ideal candidate combines technical depth with strong communication skills and the ability to translate ambiguous business questions into scalable, production ready solutions.

Ways of Working

• Hybrid work model with close collaboration alongside trading and analytics teams

• Fast paced, iterative development approach-prototype quickly, refine with user feedback, and harden solutions for production

• Strong focus on operational excellence, including secure CI/CD practices, automated testing, and production reliability

Key Responsibilities

• Design, develop, and deliver AI driven analytics for front office use cases, including seasonality analysis, correlation, regression, forecasting, and scenario modeling

• Build and maintain scalable, reusable data pipelines using Databricks and Spark (PySpark, SQL, Delta Lake, Unity Catalog)

• Perform statistical and econometric analyses on large, complex datasets such as market pricing and fundamental time series data

• Collaborate directly with business stakeholders to gather requirements, clarify objectives, and communicate insights effectively

• Develop and integrate LLM based and agentic workflows, including prompt engineering, orchestration, retrieval, and guardrails

• Productionize solutions with appropriate testing, observability, documentation, and version control

• Required Qualifications

• Hands on experience with Databricks and Apache Spark (PySpark, SQL, Delta Lake, Unity Catalog)

• Strong data engineering experience, including data ingestion, modeling, orchestration, and performance optimization

• Solid foundation in statistics, economics, or data science, particularly related to time series analysis

• Experience implementing LLM based solutions, including prompt design, retrieval workflows, and agent frameworks

• Familiarity with modern engineering practices and tooling, such as CI/CD pipelines, infrastructure as code, experimentation frameworks, and data governance

• Strong communication and collaboration skills, with the ability to work effectively with technical and non technical stakeholders

Preferred Qualifications

• Experience in commodity trading, financial trading, or energy markets

• Familiarity with market microstructure, supply demand fundamentals, and risk management concepts

• Exposure to MLOps tooling, feature stores, vector databases, and model lifecycle management

Equal Opportunity Statement

• We are an equal opportunity employer and value diversity at all levels of the organization.

• All qualified applicants will be considered without regard to race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, disability, veteran status, or any other legally protected status.

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