Top Cybersecurity Data & Analytics Jobs in Chicago, IL

Analyze complex credit and alternative data, investigate data quality issues, identify root causes, develop quality metrics and dashboards, and translate findings into business recommendations. Lead data initiatives, support business acceptance testing, create data-driven solutions, improve processes and automation, and mentor team members. The role requires advanced SQL and collaboration with business and technology stakeholders.

Provides analytics and strategic advisory support for mergers, acquisitions, and other business transactions. Analyzes contract data to identify risks, obligations, performance insights, and compliance indicators; develops algorithms, data models, pipelines, dashboards, and predictive models using Python and machine learning. Collaborates with clients and internal teams, validates data integrity and security, mentors junior staff, and delivers data-driven recommendations.

Design and govern data assets, develop pipeline specifications with field-level mapping and quality rules, document domain data models and canonical formats, design scalable databases and ETL solutions, and solve complex data problems to support Cat Digital. Hybrid work: telecommute one day per week.

Leads the enterprise data platform strategy, architecture, governance, and evolution. Manages a central data team and enables federated self-service analytics across business functions. Builds AI-ready data pipelines, RAG and Graph RAG architectures, custom data applications, observability, cost optimization, and AIOps capabilities. Requires hands-on expertise with Snowflake, dbt, modern ETL, Python, SQL, CI/CD, and Data Mesh architectures, along with 5+ years leading technical data teams.

Build and maintain cloud cost monitoring, alerting, and optimization tooling. Develop automation, cost allocation/tagging, data pipelines, dashboards, and integrations with billing APIs. Support FinOps processes, implement cost guardrails, troubleshoot cost systems, participate in on-call rotation, and collaborate with senior engineers and product teams to drive cost-efficient infrastructure and reporting.

Designs and manages scalable data pipelines, contracts, transformation layers, and analytics models. The role focuses on data governance, observability, lineage, configuration validation, and collaboration with product engineering teams. It requires processing large datasets, integrating cloud and on-premises industrial technologies, and implementing streaming and message-queuing solutions, ideally in cybersecurity or industrial environments.

The Senior Data Analyst gathers BI requirements, analyzes enterprise and offline datasets, writes and optimizes SQL queries, and builds dashboards using Power BI, Tableau, and Domo. The role translates business needs into technical specifications, designs dashboard wireframes, validates data, documents processes, and collaborates with engineering, product, and business teams. Knowledge of the US trust business is essential for interpreting data within financial and regulatory contexts.

Analyzes cybersecurity and operational data to identify trends, anomalies, risks, and performance insights. Develops executive dashboards, scorecards, KPIs, KRIs, automated reports, and reusable analytics frameworks using tools such as SQL, Tableau, and Power BI. Applies AI-enabled analytics to improve reporting efficiency and data interpretation. Partners with security, risk, compliance, technology, and infrastructure teams to translate technical findings into actionable business recommendations.

Lead and grow the Revenue Analytics team to deliver strategic sales and customer lifecycle insights. Build forecasting, pipeline, capacity, predictive models, and customer lifecycle analytics to improve revenue, retention, adoption, and expansion. Partner with GTM, Finance, Product, and Enterprise Data to create executive reporting, data governance, AI-enabled self-serve datasets, and integrated analytics that drive business outcomes and support a shift to consumption-based models.

Develops Tableau and ServiceNow dashboards, KPIs, reports, and actionable data insights. Analyzes complex datasets, investigates root causes, applies machine learning and AI for forecasting and anomaly detection, supports data governance and quality, and recommends process improvements. Collaborates with cross-functional stakeholders and communicates findings to technical and non-technical audiences.