Top Data Management Jobs in Chicago, IL

Lead data analytics strategy, mine and analyze large-scale datasets, build and validate models, improve reporting and operational processes, evaluate products and marketing initiatives, and consult on data systems. Manage and mentor junior analysts, collaborate across business units, oversee concurrent projects, and apply business intelligence tools to support customer experience and organizational decision-making.

Leads data engineering and analytics engineering teams delivering production pipelines, curated data products, semantic models, dashboards, and governed Databricks lakehouse capabilities. Owns platform administration, data quality, observability, security, cost optimization, reliability, and engineering standards. Manages internal and external resources, mentors engineers, drives AI-assisted development, partners with stakeholders, and reports roadmap progress to leadership. Requires strong hands-on Databricks expertise, technical leadership, advanced SQL, data modeling, CI/CD, and up to 5% travel.

Leads the Data Engineering team and sets technical direction for the company’s data platform. Owns Snowflake, PostgreSQL, pipelines, modern ELT tooling, Medallion architecture, reliability, scalability, cost optimization, data quality, observability, governance, and security. Partners across Engineering, Analytics, Product, Finance, Risk, and Marketing to deliver reusable data solutions. Develops engineers, establishes standards, communicates technical tradeoffs, and builds a long-term platform roadmap supporting analytics, automation, and AI.

Leads business and system requirements gathering, stakeholder solutioning, documentation, configuration, troubleshooting, quality assurance, testing, and release-note coordination. The role supports customization requests, reviews configurations, oversees project testing, monitors junior business analysts, and helps deliver solutions for fintech and financial-services clients.

Manage data governance and risk programs for Global Payment Networks. Analyze large datasets, build and validate models, improve data and reporting processes, establish controls, support privacy and regulatory compliance, and lead cross-functional projects. The role also includes mentoring junior analysts, managing concurrent initiatives, and consulting on data systems, product testing, and business intelligence solutions.

Design, build, and operate scalable cloud data pipelines, platforms, and applications. The role involves distributed data processing, data modeling, relational and NoSQL databases, data security, observability, orchestration, and real-time workloads. The engineer will collaborate with product and engineering teams, establish reusable data engineering patterns, communicate technical outcomes, mentor data professionals, and influence solutions using technologies such as Python, Spark, Databricks, and Snowflake.

Design, build, and support scalable cloud data platforms, pipelines, and applications. The role involves distributed data processing, data modeling, relational and NoSQL databases, data security, observability, orchestration, and real-time pipelines. It also requires influencing cross-functional teams, mentoring data professionals, establishing engineering standards, and communicating technical outcomes to stakeholders.

Leads data engineering teams and technical strategy for scalable cloud data platforms. Oversees architecture, pipelines, data models, quality, observability, and operational standards across Databricks, Spark, Python, and Snowflake environments. Mentors engineers, drives large-scale data initiatives, evaluates platform choices, and collaborates with product and software teams to deliver reliable data solutions.

Leads data analysis and AI-readiness initiatives for the personal loans business, including data governance, quality, automation, reporting, and analytics. Manages complex data analysis projects, improves processes and customer experiences, evaluates products and marketing initiatives, and collaborates across business units. Mentors junior analysts and contributes to data system design, business intelligence, and strategic testing.

Leads data analytics and AI-readiness initiatives for the personal loans business. Responsibilities include improving data governance and quality, automating monitoring controls, building data abstraction layers, analyzing large databases, evaluating products and processes, enhancing business intelligence, and mentoring junior analysts. The role involves cross-functional collaboration, strategic testing, reporting improvements, and consulting on data systems while managing concurrent projects.

Manages data governance and pricing-related risks by overseeing processes, controls, reporting, documentation, and improvement initiatives. The role analyzes process data, identifies gaps, resolves policy-related issues, collaborates on enterprise projects, represents departmental interests, and trains junior staff and internal stakeholders. Responsibilities include maintaining procedures and diagrams, recommending process changes, supporting executive reporting, and ensuring adherence to data management and governance frameworks.

Lead and grow a global data engineering team while establishing foundational data platforms and engineering standards. Design and oversee GCP-based pipelines, medallion data models, DataOps, monitoring, SLAs, CI/CD, governance, and data quality practices. Drive AI adoption across engineering workflows and build reliable, AI-ready data. Partner with business and technology stakeholders to prioritize roadmaps, deliver scalable solutions, and support data democratization.

Lead design and implementation of data infrastructure, pipelines, and warehouses using Azure Data Factory, Databricks, and Snowflake. Manage data modeling, quality, security, and analytics frameworks. Lead client accounts, mentor teams, and drive innovation to deliver data-driven business insights.

Lead and coach teams to design, code, test, and deliver software solutions driving digital transformation for tax clients. Translate requirements into technical specs, perform code reviews, troubleshoot complex issues, maintain client relationships, and promote innovation and systems thinking to validate outcomes and improve products.

Lead design and implementation of scalable data infrastructure, pipelines, and transformations using cloud platforms. Build and optimize data warehouses (Snowflake, Databricks), orchestrate workflows (Airflow, Hadoop), ensure data quality and security, and coach teams to deliver analytics solutions that drive tax practice insights and client outcomes.

Lead development and execution of data-driven strategies, manage project planning and delivery, mentor and coach team members, ensure quality and ethical standards, design cloud data architectures and governance frameworks, analyze complex datasets to produce actionable insights, and drive continuous improvement using advanced analytics and modern data technologies.

Leads client-focused data analytics initiatives within PwC’s Risk & Regulatory practice. Develops business intelligence, visualization, and advanced analytics solutions using Python, Oracle Business Intelligence, QlikView, and Spotfire. Builds stakeholder relationships, validates outcomes, drives process improvement, and applies systems thinking to solve complex business challenges. Oversees scalable deployments and coaches teams through ambiguous situations while delivering strategic insights and improved client performance.

Lead development and deployment of data-driven software solutions within the Tax practice. Manage client relationships, guide teams in design/coding/testing, enforce coding standards, implement CI/CD, integrate enterprise applications, conduct code reviews, mentor staff, and ensure projects are planned, budgeted, executed, and completed to meet client expectations.

Lead development and implementation of data governance strategies, manage client accounts and deliverables, supervise and mentor teams, analyze data to inform business decisions, ensure compliance with firm standards, and identify improvements in data management processes.

Analyzes AML and KYC data, builds regulatory reporting dashboards, develops KPIs and KRIs, identifies compliance risks and trends, improves processes and reporting, and advises leadership and business units. The role manages complex datasets, supports AML program health analysis, collaborates across teams, and contributes to projects involving data quality, operational efficiency, and compliance risk management.

Own and operate Toast’s enterprise data governance program, including data domain ownership, governance council coordination, policy compliance, business glossary management, metadata standards, catalog adoption, maturity assessments, and data literacy training. The role partners with business stakeholders, data stewards, catalog teams, and leadership to improve data trust, compliance, discoverability, and quality. It requires governance, metadata, SQL, data catalog, program management, and workshop facilitation experience.

Manages the design, reliability, security, and ongoing development of the enterprise data warehouse and integrations in SQL Server and Azure. Leads data architecture, Python automation, data quality, HIPAA-compliant processes, source-system connectivity, deployment standards, stakeholder delivery, and team growth. Partners across clinical, financial, payroll, and operational functions to deliver reliable data solutions.

Lead multiple data engineering scrum teams responsible for batch and streaming pipelines, governed data products, data quality, reliability, and enterprise reporting assets. Set technical direction, roadmap priorities, engineering standards, and delivery practices across Corporate Functions data. Partner with business, product, analytics, governance, and security stakeholders while recruiting, coaching, and developing engineers. Oversee Azure, Python, Spark, Kafka, CI/CD, observability, incident management, data governance, and cloud cost planning.

The role involves leading the data governance team, managing IT projects, collaborating with stakeholders, and ensuring continuous improvement of processes. Responsibilities include strategic planning, client management, and optimizing resource utilization, while overseeing governance activities and departmental management.

Leads data governance, risk mitigation, analytical tool validation, and program development for Global Payment Networks. Responsibilities include planning validation projects, assessing analytical methodologies and tool risks, researching industry practices, preparing reports and presentations, and coaching junior staff. The role requires managing concurrent projects and applying data analytics, risk management, statistical, and project management expertise to develop enterprise-wide controls and processes.