Data & Analytics Jobs in Chicago, IL (Now Hiring) — 2,452 open — Page 8

The Data & AI Engineer is a hands-on builder who develops BGL’s data platform, analytics, and AI integrations. The role is a shared resource reporting to both the Director of Information Technology and the Director of Enterprise Intelligence & AI: the IT function provides the governed platform and security controls, while the Enterprise Intelligence & AI function drives the analytics and AI use cases the engineer builds and holds the administrative reporting line. The role is designed to evolve with the firm’s AI maturity: from day one it combines data platform work with hands-on AI enablement — integrations, retrieval pipelines, and support for AI tools already in deployment — and grows into building the firm’s AI applications as the roadmap advances.

Working Model & Reporting

• Administrative line — Administrative and HR matters (time, expenses, and reviews) run through the Director of Enterprise Intelligence & AI; platform access provisioning and security controls remain owned and governed by IT.
• Division of labor — This role builds on the data platform; the Systems & Cloud Administrator administers it (access, security, cost, backup). The engineer develops pipelines, models, and solutions within IT’s governance and compliance guardrails.

Key Responsibilities

Data Engineering

• Pipelines — Design, build, and maintain ELT pipelines using Fivetran into Snowflake, ingesting line-of-business and SaaS sources; handle schema evolution, monitoring, and failure recovery.
• Modeling — Develop curated, well-documented data models and transformation layers that make firm data consistent, discoverable, and reliable for downstream use.
• Quality & lineage — Implement data-quality checks, testing, and lineage documentation appropriate to a regulated environment.

Analytics & Business Intelligence

• Reporting enablement — Build semantic layers and datasets that power reporting, partnering with the Data & Analytics Specialist who develops business-facing reports and dashboards.
• Tableau ownership — Own all technical aspects of the firm’s Tableau environment, including site and user administration, permissions, published data sources and connectivity (Salesforce, Snowflake, SharePoint/OneDrive), extract and refresh schedules, and performance tuning.
• Data sources & dashboards — Architect and maintain the published data sources, connections, and certified datasets that power the firm’s dashboards; build and support dashboards in partnership with business stakeholders, who own requirements and visual design.
• Self-service — Enable governed self-service analytics with clear definitions, certified datasets, and usage documentation.

AI Data Layer & Application Development

• AI integration — Build the data foundations and technical integrations for the firm’s AI initiatives (e.g., retrieval pipelines, API integrations, Azure AI services), as directed by the Enterprise Intelligence & AI roadmap.
• AI application development — As the firm’s data foundation and AI roadmap mature, prototype and build AI-powered solutions on the data platform (e.g., document intelligence, deal and relationship insights, internal copilots and agentic workflows), moving successful prototypes into production within compliance guardrails.
• Evaluation & reliability — Establish testing and evaluation practices for AI outputs (accuracy, retrieval quality, hallucination monitoring) so AI solutions meet the standards of a regulated firm.
• Compliance alignment — Develop within IT-owned security and compliance controls — sensitivity labels, DLP, audit, and retention — so AI workloads remain examiner-ready.
• AI consumption & cost — Instrument and monitor AI and data platform consumption (Snowflake credits, Azure AI usage), reporting cost trends and optimization opportunities.

Required Qualifications

• 4+ years of hands-on data engineering experience in production environments.
• Strong SQL and Python; demonstrated experience building and operating Snowflake-based platforms and managed ELT (Fivetran or comparable).
• Hands-on Tableau experience with an emphasis on published data source architecture, connectivity, and performance; dashboard development proficiency; site administration experience preferred, or the aptitude to take ownership of it quickly.
• Experience integrating cloud AI services (Azure OpenAI / Azure AI services or comparable) into data workflows.
• Working knowledge of data governance, access control, and security practices; comfort operating within compliance guardrails.
• Strong documentation and communication skills; able to serve stakeholders with transparency.

Preferred Qualifications

• • Experience in financial services or another regulated industry.
  • dbt or comparable transformation framework; CI/CD for data workloads; infrastructure-as-code exposure.
  • Experience with Power BI and/or Microsoft Fabric semantic models and reporting enablement.
  • Familiarity with Microsoft Purview, sensitivity labels, and DLP as they apply to data and AI workloads.
  • SnowPro Core, DP-600 (Fabric Analytics Engineer), DP-203, or AI-102 certifications

#LI-LP1