Data & AI Engineer – Equities Technology

Imea; Chicago (IL); Hybrid; USD 130,000 - 161,000; Full time

Benefits offered by this job

Medical, dental and vision coverage

Employer-paid disability and life保险

401(k) with profit sharing

Paid time off

Maven family & fertility benefit

Parental leave

Job summary

Imea is seeking a Data & AI Engineer in Chicago to design, build, and maintain scalable data pipelines and AI-enabled platforms across trading, research, and client services.

You will drive data reliability, governance, and secure productionization of AI/LLM features within a regulated environment, collaborating with cross‑functional teams to deliver production-ready solutions.

Qualifications

• Bachelor’s degree in information technology or related field.
• 4–6+ years of hands-on experience with Databricks, Spark, Azure Data Factory, Azure Synapse, Python, ADLS and Azure Functions.
• Strong experience designing and managing Synapse/ADF pipelines, activities, and linked services.
• Proven ability to build full and incremental data loads from Azure and on-prem data sources.
• Experience designing reusable ETL/ELT frameworks and orchestrating pipelines across ADF/Synapse/Databricks.
• Experience implementing LLM-enabled or RAG-based solutions in production environments.
• Proficiency with REST APIs, data gateways, and third-party system integrations.
• Strong SQL skills with data modeling, analytical storage, and performance tuning.
• Experience with Azure DevOps and YAML-based CI/CD pipelines.
• Familiarity with Azure Key Vault, automation runbooks, Logic Apps, and cloud security best practices.
• Strong communication, collaboration, and problem-solving skills.

Responsibilities

• Design, build, and maintain scalable data pipelines using Databricks, Azure Data Factory, and Azure Synapse.
• Implement ETL/ELT workflows for structured and unstructured financial data across on‑prem and cloud.
• Ensure data quality, lineage, governance, security, and observability across pipelines and storage.
• Design and optimize data models and analytical schemas (star/snowflake, partitioning).
• Build reusable ingestion and transformation frameworks to support analytics and AI workloads.
• Build and deploy AI-enabled services, agents, and workflows for research, trading, and client service.
• Integrate AI capabilities into applications via APIs, batch jobs, and event-driven workflows.
• Productionalize AI/DS POCs into secure, scalable services for regulated environments.
• Optimize prompts, embeddings, orchestration, and inference workflows for performance and cost.
• Establish operational practices for AI solutions including monitoring and runbooks.
• Collaborate with product, software, and data science teams to translate AI into production.

Skills

Databricks

Spark

Azure Data Factory

Azure Synapse

Python

ADLS

Azure Functions

SQL

REST APIs

Education

Bachelor’s degree in information technology or related field

Tools

Azure DevOps

YAML

Azure Key Vault

Logic Apps

Job description

Job Description

We’re seeking a Data & AI Engineer to design, build, and maintain intelligent, scalable data and AI‑enabled platforms supporting our Equities business across Trading, Research, and Sales. This role spans the full software development lifecycle and is responsible for moving data and AI solutions from concept through production, while ensuring reliability, security, and compliance with firm standards.

The ideal candidate brings strong data engineering fundamentals combined with hands‑on experience integrating AI and LLM‑based capabilities into production systems in a regulated environment.

The role will be based in Chicago with a hybrid work schedule.

Key Responsibilities

Data Engineering & Platform Foundations

• Design, build, and maintain scalable data pipelines using Databricks, Azure Data Factory, and Azure Synapse
• Implement robust ETL/ELT workflows for structured and unstructured financial data across on‑prem and cloud platforms
• Ensure data quality, lineage, governance, security, and observability across all pipelines and storage layers
• Design and optimize data models and analytical schemas (star/snowflake, partitioning, distribution strategies)
• Build reusable ingestion and transformation frameworks to support analytics and AI workloads

AI Integration & Agentic Workflows

• Build and deploy AI‑enabled services, agents, and workflows supporting equity research, trading, sales, and client service use cases
• Implement LLM‑based and agentic patterns, including Retrieval‑Augmented Generation (RAG), using proprietary firm data
• Integrate AI capabilities into existing applications and platforms via APIs, batch jobs, and event‑driven workflows
• Partner with Data Science and business stakeholders to translate AI concepts into production‑ready solutions

AI Enablement & Productionization

• Productionalize AI and Data Science POCs into secure, scalable, and monitored services suitable for regulated environments
• Optimize prompts, embeddings, orchestration logic, and inference workflows for accuracy, performance, cost, and reliability
• Ensure AI solutions meet firm standards for security, auditability, explainability, and compliance
• Establish operational practices for AI solutions, including monitoring, alerting, lifecycle management, and runbooks

Cloud Modernization & DevOps

• Support migration of legacy data and application solutions (SQL, SSIS, Synapse, custom ETLs) to modern Azure‑native architectures
• Implement CI/CD pipelines using Azure DevOps and YAML, following infrastructure‑as‑code and automation best practices
• Leverage Azure services (Functions, Key Vault, Logic Apps, Automation Runbooks) to build secure, reliable, and maintainable solutions
• Develop operational dashboards to monitor pipeline health, SLAs, system performance, and cloud spend

Collaboration & Delivery

• Work closely with Product Managers, Software Engineers, Data Scientists, and business stakeholders to define functional and technical requirements
• Participate in Agile ceremonies, sprint planning, and retrospectives
• Lead testing of new and modified software, analyze issues, and resolve defects efficiently
• Document technical designs, integrations, and maintain operational playbooks and runbooks
• Monitor industry trends in data engineering, cloud platforms, and AI, and recommend adoption where aligned with firm strategy

Essential Qualifications

• Bachelor’s degree in information technology or related field
• 4-6+ years of hands‑on experience with Databricks, Spark, Azure Data Factory, Azure Synapse, Python, ADLS, and Azure Functions
• Strong experience designing and managing Synapse/ADF pipelines, activities, and linked services
• Proven ability to build full and incremental data loads from Azure and on‑prem data sources
• Experience designing reusable ETL/ELT frameworks and orchestrating pipelines across ADF/Synapse/Databricks
• Experience implementing LLM‑enabled or RAG‑based solutions in production environments
• Proficiency with REST APIs, data gateways, and third‑party system integrations
• Strong SQL skills with experience in data modeling, analytical storage, and performance tuning
• Experience with Azure DevOps and YAML‑based CI/CD pipelines
• Familiarity with Azure Key Vault, automation runbooks, Logic Apps, and cloud security best practices
• Strong communication, collaboration, and problem‑solving skills

Preferred Qualifications

• Hands‑on experience with Azure AI Services, including OpenAI, embeddings
• Familiarity with Microsoft Fabric (future roadmap alignment)
• Proficiency in ASP.NET, .NET Core, or C#
• Background in financial services, capital markets, or other regulated environments

A reasonable estimate of the current base salary range at time of posting is below. Base salary does not include other forms of compensation or benefits. Actual base salary within the specified range is based on several factors, including but not limited to applicant’s skills, prior relevant experience, specific degrees and certifications, job responsibilities, market considerations and, if applicable, the location of the position.

This role is eligible for either a discretionary annual bonus (based on company, business unit and individual performance) and/or commission-based incentives.

Our featured benefit offerings include medical, dental and vision coverage, employer paid short & long-term disability and life insurance, 401(k), profit sharing, paid time off, Maven family & fertility benefit, parental leave (including adoption, surrogacy, and foster placement), as well as other voluntary benefits.

Salary Range

$130,000-$160,800 USD

Tagged as: Hybrid