Top Data Management Jobs in Chicago, IL

Lead a team evaluating new and existing data assets, standardize due-diligence and analytical methodologies, validate data quality and business value, partner with Product and Technology to support onboarding and OneTru cataloging, establish governance and lineage standards, and coach team members to drive data-driven product and revenue decisions.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Lead and mentor a data engineering team building scalable customer-focused data solutions. Hands-on technical ownership, architecture guidance, and delivery of data ingestion, transformation, and reporting. Advance AI-enabled development practices, set technical standards, and foster a collaborative, accountable engineering culture to improve speed, quality, and reliability.

Lead a team to analyze large-scale datasets, build and validate models, improve reporting and operational efficiency, design data/storage systems, run strategic tests, and collaborate across business units to drive analytics strategy and customer experience.

Lead validation of enterprise analytical tools: refine validation framework, plan and execute projects, assess methodology quality and risk, prototype best practices, communicate findings, and coach junior staff.

Lead design and rollout of a fit-for-purpose data governance program: manage data lifecycle, implement governance frameworks and tools, drive data catalogs/lineage, upskill stewards, define KPIs, and partner cross-functionally to improve data quality, compliance, and usability.

Lead a team delivering enterprise-wide model risk reporting and AI-driven automation. Build and deploy scalable ML/AI solutions, conversational reporting, multi-agent workflows, and centralized data integrations. Drive analytics strategy, validate models and data, improve reporting and operational efficiency, and collaborate across business units.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Manage and improve corporate giving data systems: build and maintain Tableau/Excel dashboards, respond to ad hoc data requests, clean and govern community data, administer Bonterra/CyberGrants, and lead project management for giving programs and strategic initiatives while partnering with enterprise stakeholders.

Lead a small data engineering team and own market data platforms from ingestion through delivery. Build and maintain KDB+/Q time-series systems, ensure data correctness, low-latency decoding, replay/recovery, and reliable distribution to downstream consumers. Write production code, review designs, improve observability, and prepare the platform for AI-driven consumers.

Own the Industrial platform’s data infrastructure, datasets, dashboards, models, and AI-enabled analytical workflows. Deliver investor and occupier business-development insights, supply-chain mapping, surveys, executive reporting, presentations, and pursuit support. Partner with Research, Sales Enablement, technology, operations, brokers, and leadership to improve data integrity, self-service reporting, platform capabilities, and automation. Coordinate cross-functional initiatives and translate quantitative analysis into actionable narratives for senior leaders and clients.

Lead and scale a distributed data engineering organization: design and maintain cloud-native data infrastructure, build ETL/ELT pipelines and event streams, ensure data quality and observability, deliver dashboards and analytics tools, partner with product and business stakeholders, and manage analytics project prioritization and team performance.

Manage procurement data and reporting, including spend analytics, data integrity, taxonomy, dashboards, integrations, and ad hoc analysis. Partner with sourcing, FP&A, finance, and leadership to improve reporting, track savings and spend, monitor purchase orders and invoices, and support Travel & Expense strategy. Oversee Ignite and related procurement tools while developing standardized metrics, automated reporting cadences, and Looker visualizations.

Lead design and build of a cloud-based data platform; manage and mentor data engineering staff; define engineering standards, data governance, and access controls; partner with stakeholders to deliver scalable, reliable data pipelines and platform services for analytics and AI.

Manages the daily operations and maturation of a federated enterprise data governance program. Leads governance councils and stewardship groups, defines roles, develops policies and guidance, drives stakeholder adoption and training, and advances data quality, metadata, lineage, and issue resolution practices. Partners with legal, privacy, security, compliance, business, technical, and external stakeholders while maintaining governance documentation, monitoring program performance, and coordinating approvals and improvements.

Lead and manage a remote Data Engineering team to build scalable data pipelines and lakehouse solutions. Own execution of Medallion architecture using Databricks, Boomi/Rivery, dbt, Delta Lake and SQL Server; implement DataOps, CI/CD, observability, and stakeholder intake while growing engineers and improving team maturity.

Manage transportation data integrity from intake through ETL and business intelligence platforms. Review and correct data errors, resolve quality and flow issues, analyze large transportation datasets, and create KPI reporting solutions. Deliver client business reviews covering spend, trends, savings, and market impacts. Serve as a client contact while collaborating with audit, finance, development, and analytics teams to improve reporting tools, software, and customer outcomes.

Lead the master data management function, set data standards and governance, manage MDM analysts, ensure data quality across item/vendor/pricing/location domains, partner with cross-functional teams, support system implementations and migrations, and drive continuous improvement in retail data processes.

Lead and develop Analytics Engineers responsible for shared data foundations, platform capabilities, semantic models, developer tooling, and AI-enabled workflows. Define the team vision, operating model, roadmap, standards, and success measures. Partner cross-functionally to prioritize initiatives, improve adoption, guide architecture, and deliver scalable data assets and automation. Drive responsible AI-assisted development, data reliability, testing, documentation, observability, and cost management while contributing hands-on when needed.

Lead a remote analytics team to deliver dashboards, data products, and decision-support tools. Oversee project plans, stakeholder engagement, data platform modernization, ETL/automation, Tableau/Power BI deployments, statistical modeling, QA, metadata, and staff mentoring to support federal social service programs.

Leads and scales a global data engineering and analytics team while remaining hands-on with architecture, pipelines, data quality, dimensional modeling, dashboards, reporting, and customer-facing deliverables. Owns the analytical data platform supporting clinical, operational, product, financial, and customer data. Partners with cross-functional stakeholders, investigates complex data issues, improves platform reliability and security, and mentors engineers.

Manage Advancement data systems, donor and prospect information, fundraising portfolios, reporting, analytics, gift processing, and reconciliation. Maintain donor database integrity, security, and adoption; conduct prospect research and wealth screening; produce dashboards and KPI reports; train staff; and collaborate with Finance and fundraisers to optimize donor engagement and fundraising operations.

Partner with Corporate Partnerships to centralize data, design dashboards and analytics tools, automate workflows, optimize CRM, and lead cross-functional projects to drive data-informed partnership decisions.

Lead a scrum team of 5–7 data engineers to design, build, and operate Azure Databricks Lakehouse solutions. Set technical standards, drive data quality, oversee ETL/streaming pipelines, code reviews, CI/CD, and partner with architects and business stakeholders to deliver scalable, governed data products.

Lead and manage data transformation and migration projects, design and build automated data quality monitoring tools, analyze/clean/transform data using SQL/Python/JavaScript, collaborate with cross-functional teams, document mappings and processes, troubleshoot conversion issues, and apply AI and automation to improve data integrity and efficiency.