Top Senior Data Management Jobs in Chicago, IL

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.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, experimentation, campaign reporting, retention analysis, churn modeling, and segmentation. Partners with Marketing and Finance to establish performance goals and translate complex data into actionable recommendations. Automates reporting using analytics platforms, marketing automation tools, experimentation methods, and AI-enabled workflows while identifying opportunities to grow and retain high-value consumers.

Leads LTK’s Data Engineering team, owning technical direction, architecture, pipelines, data products, governance, quality, reliability, and platform modernization. Manages and develops engineers, drives roadmaps and complex initiatives, partners with cross-functional stakeholders, and balances scalability, security, performance, cost, and business priorities. Establishes engineering standards, improves operational practices, manages risks and dependencies, and builds trusted, reusable data capabilities supporting analytics, reporting, products, and AI use cases.

Leads a team of 5–8 data engineers and analysts while remaining hands-on with Databricks and Azure data platforms. Owns scalable pipelines, Lakehouse architecture, data products, quality, governance, reliability, security, and cost management. Oversees hiring, coaching, performance, delivery prioritization, agile execution, production health, incident response, stakeholder communication, and cross-team collaboration. Helps shape global data engineering strategy, standards, technology adoption, and platform evolution.

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.

Build and lead Inovalon’s third-party data governance program, including data asset inventory, licensing controls, contractual rights management, data intake and release governance, audit readiness, compliance monitoring, and KPI reporting. Partner with Legal, Privacy, Procurement, and business leaders to manage data usage, renewals, access revocation, disposition, and downstream obligations. Develop a governance team while applying expertise in healthcare data, HIPAA, de-identification, and data licensing.

Lead and implement hands-on data governance across the Data Platform: build and operate the enterprise catalog, automate lineage, embed data quality checks, configure Snowflake governance, manage access workflows and event contract governance, create governance metrics and dashboards, define standards and operating model, enable domain teams, and hire and lead a small governance function.

Manage data analysis for transaction monitoring, risk identification, and compliance. Analyze high-volume transaction data using SQL, Python, Splunk, and visualization tools; conduct root-cause investigations; design risk data architectures; identify process and reporting improvements; advise business and product teams; and translate technical findings into executive recommendations. The role also involves stakeholder liaison, regulatory alignment, data integrity, and managing concurrent analytical projects.

Leads the customer master data governance program and serves as business owner for the Informatica MDM platform. Oversees governance policies, data quality, customer hierarchies, stewardship operations, source onboarding, platform enhancements, and AI-enabled matching and deduplication. Partners with business, IT, technical teams, and external providers to define requirements, manage priorities, resolve issues, and improve data processes. Performs hands-on testing, validation, reconciliation, and user acceptance activities before platform changes are deployed.

Designs, builds, tests, and supports enterprise data pipelines and Snowflake archival solutions for acquisitions, integrations, reporting, compliance, and analytics. Translates business and technical requirements into mappings, transformations, quality rules, and deployment plans. Collaborates with architecture, security, infrastructure, application, business, and vendor teams. Oversees validation, monitoring, documentation, cutover, go-live readiness, hypercare, and operational handoff while improving reusable, secure, cost-efficient data engineering practices.

Leads data governance for acquired-company integrations, embedding ownership, stewardship, quality, metadata, lineage, retention, privacy, legal holds, and compliant data use across structured and unstructured content. Establishes data inventories, quality rules, retention and disposal processes, governance controls, and readiness metrics. Partners with business, technology, legal, privacy, risk, security, and implementation teams, while producing executive reporting and supporting governance technology adoption.

Leads data engineering, business intelligence, and analytics teams; oversees data pipelines, integration infrastructure, database architecture, CI/CD practices, and enterprise data platform strategy. Partners with business and technology stakeholders to define requirements, improve data capabilities, maintain Ubuntu-based services, and deliver reporting and KPIs to leadership. Responsible for team hiring, development, mentoring, operational health, and technical execution across analytics and data integration platforms.

Lead data strategy, architecture, and modeling for high-volume transactional network platforms. Build monitoring and anomaly-detection frameworks, optimize operational data schemas, align local assets with enterprise data strategy, communicate findings to stakeholders, and mentor technical staff.

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

Leads and develops a Data Platform engineering team while owning delivery of complex data initiatives. The role establishes delivery discipline, assesses technical and implementation risks, partners cross-functionally, and drives production reliability, data quality, observability, incident management, and on-call readiness. It also guides the evolution of scalable data ingestion, transformation, lakehouse, cloud architecture, governance, and reusable platform capabilities.

Leads data governance for acquired-company integrations, embedding governance, ownership, quality, metadata, lineage, retention, privacy, legal hold, and compliance requirements across structured and unstructured data. Establishes data inventories, stewardship models, quality controls, retention schedules, and approval processes; coordinates with business, technology, legal, risk, privacy, and security stakeholders. Supports migration, archival, modernization, analytics enablement, governance tooling, executive reporting, and cross-functional transformation readiness.

Lead validation of enterprise-wide analytical tools for risk management: plan and execute validation projects, assess methodology quality and tool risk, prototype best practices, communicate findings, and coach junior staff.

Designs, builds, tests, and supports enterprise data pipelines for acquired-company system integration and Snowflake archival. Translates business and technical requirements into mappings, transformations, quality controls, monitoring, and deployment plans. Collaborates with architecture, security, infrastructure, application, business, and vendor teams to deliver governed, reusable data solutions. Supports migration, cutover, validation, documentation, hypercare, and operational handoff while improving automation, performance, cost efficiency, and data observability.

Leads enterprise data engineering solutions for financial services clients using Snowflake, Databricks, SQL, and Python. Designs and optimizes ELT/ETL pipelines, data models, analytical datasets, orchestration, governance, and performance solutions. Mentors data engineers, manages technical priorities and deliverables, reviews designs and code, and works directly with business and technology stakeholders on accounting, tax, finance, risk, and regulatory reporting initiatives.

Manages corporate real estate spatial data, CAD drawings, CAFM systems, space allocation models, reporting, data governance, and system administration. Supports project management, occupancy planning, and move management by maintaining accurate as-built drawings, monitoring space data, establishing global standards, coordinating system integrations, training users, and recommending process improvements. Requires expertise in CAD/CAFM, drafting, space planning, and corporate real estate data management.

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.

Leads a team of data engineers responsible for building and scaling Niche’s data platform. Oversees data pipelines, warehouse layers, platform reliability, data quality, monitoring, and engineering best practices. Manages roadmap execution, Agile rituals, cross-functional collaboration, hiring, mentoring, and career development. The role also drives process improvements, operational excellence, scalability, and delivery of secure, observable data solutions supporting analytics, reporting, content, and operational systems.

Leads customer data engineering strategy, delivery, team development, and roadmapping. Oversees data-driven product improvements, digital programs, quality initiatives, budgets, cybersecurity remediation, and portfolio management. Manages, mentors, and grows data engineering teams, including contractor teams, while guiding customer data platforms, omnichannel identity resolution, complex data modeling, and personalization-focused data science capabilities. Partners across the organization to execute strategic initiatives and build team capability.

Leads a data engineering team responsible for designing, developing, testing, deploying, and maintaining scalable data products and platforms. Sets technical direction, manages team performance and development, establishes engineering standards, and oversees data quality, security, governance, and operational excellence. Partners with product owners, enterprise architecture, information security, data governance, and business stakeholders to deliver data solutions. Defines team strategy and roadmap, evaluates emerging technologies, and communicates metrics and progress to senior leadership.

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.