Top Senior Data & Analytics Jobs in Cleveland, OH

Owns ERP data migration from legacy systems to IFS Cloud, including extraction, profiling, cleansing, mapping, mock loads, reconciliation, cutover, and business sign-off. Establishes enterprise master data governance for items, customers, and vendors. Builds Microsoft Fabric data pipelines and Power BI models, automates validation, and maintains data quality controls. Collaborates with Finance, Operations, Supply Chain, IT, and implementation partners while documenting standards, training data owners, and supporting agile delivery.

Leads enterprise information architecture, business intelligence, and data warehouse strategy and delivery. Oversees BI and data warehouse teams, establishes roadmaps and governance, mentors technical staff, manages project priorities, and ensures high-quality implementation. Designs enterprise data models, datamarts, metadata, ETL processes, reporting strategies, and integration artifacts. Partners with business and technology stakeholders to align data solutions with strategic goals, improve adoption, track value, and drive continuous improvement.

Lead enterprise product data governance strategy, standards, ownership models, quality KPIs, and executive reporting. Drive organizational change, process maturity, continuous improvement, and cross-functional alignment across Engineering, Product Management, Supply Chain, Operations, IT, and Data Management. Support Windchill adoption, MBOM expansion, ERP readiness, and Digital Thread transformation while improving data quality, accountability, adoption, and business outcomes.

The Business Intelligence Engineer designs, builds, deploys, and supports BI solutions, data marts, analytics platforms, ETL processes, dashboards, and reports. The role develops SQL queries, stored procedures, functions, and views; resolves data quality issues; troubleshoots PostgreSQL, BigQuery, and BI tools; documents data mappings and systems; supports business stakeholders; and mentors peers. The position also improves data accuracy, integrity, security, and platform performance while following the software development life cycle.

Analyzes marketing performance, ROI, attribution, segmentation, cohorts, and testing across channels. Builds dashboards and reports, ensures data quality and lineage, partners with engineers and vendors on marketing data pipelines, and translates findings into strategic recommendations. Uses AI tools, SQL, statistical analysis, and business intelligence platforms to support demand generation, lifecycle marketing, and executive decision-making while maintaining privacy and regulatory compliance.

Leads a team responsible for Oracle BI administration, architecture, development, data warehousing, and global ERP reporting. Provides strategic direction, manages BI implementations and projects, gathers and validates requirements, improves reporting processes, evaluates Oracle technologies, and guides SQL and PL/SQL development. The role also supports stakeholder collaboration, training, presentations, cross-functional leadership, and up to 25% domestic and international travel.

Leads ERP data migration and master data governance for an IFS Cloud implementation. Responsibilities include extracting, profiling, cleansing, mapping, transforming, loading, and reconciling manufacturing, finance, supply chain, and transactional data. Builds Microsoft Fabric pipelines and Power BI models, establishes data quality standards, manages cutover readiness, supports integrations, and coaches business data owners. Requires hands-on ERP implementation experience, advanced SQL, and strong data engineering and governance capabilities.

Leads Northwest Bank’s enterprise data governance program, including data policies, quality rules, lifecycle management, metadata, master data, stewardship, governance tooling, and remediation. Facilitates Data Working Groups, investigates root causes, manages governance metrics and reporting, demonstrates tools, documents processes, and supports training. Partners across a matrixed organization to ensure data assets meet standards, controls, regulatory requirements, and business needs.

Build instrumentation and batch/streaming ETL/ELT pipelines and REST API integrations to generate audience and trigger data for CRM/marketing automation. Ensure data quality, monitoring, and reliability at scale while collaborating with CRM, campaign, and operations teams.

Use quantitative methods to measure offline and digital marketing impact. Deliver analyses, recommendations, and presentations to clients. Perform project-based analytics (marketing mix modeling, multi-channel attribution, digital analytics, pricing/promotion, demand forecasting), lead and grow a team, and travel extensively for client work.