Top Data & Analytics Jobs in Cleveland, OH

Designs and maintains enterprise data architecture, including data lakes, warehouses, integrations, migrations, orchestration, and data management protocols. Partners with architects, DBAs, BI teams, product leaders, and business stakeholders to support analytics and data science. Requires deep experience with cloud data environments, Azure SQL, Microsoft Fabric, Spark, Hadoop, PySpark, SparkSQL, security protocols, and enterprise data integrations.

Design and build scalable data infrastructure, including lakehouse architecture, ClickHouse deployments, ETL/ELT pipelines, and data models connecting Postgres with analytics systems. Establish data quality, observability, performance, cost, and reliability standards. Collaborate with product and engineering teams, define data contracts and specifications, support real-time analytics, and use AI-assisted coding and LLMs to accelerate pipeline development and transformation.

Designs and operates data infrastructure for a clinical trial platform. Builds pipelines that extract, normalize, validate, and link information from clinical documents and publications into Aurora and GraphDB. Develops embeddings, vector search, RAG workflows, data-serving APIs, lineage tracking, and regulatory audit trails. The role also requires AWS-based orchestration, clinical data quality controls, biomedical knowledge graph modeling, and deployment automation using infrastructure-as-code and containerization.

Leads and develops a data engineering team responsible for ingestion, Snowflake administration, orchestration, CI/CD, data integrations, and platform reliability. Owns technical strategy, production operations, access controls, cost management, incident response, and engineering standards. Partners with product, analytics engineering, DevOps, and business stakeholders to deliver scalable data solutions. Mentors engineers, sets goals, prioritizes work, and supports organizational growth.

Work with clients and technology teams to gather and translate business requirements into technical user stories and solutions, propose process improvements, and communicate effectively with stakeholders. Assist in analytical solution delivery and may write/execute SQL queries.

Analyze marketing and customer data to measure campaign impact, uncover customer insights, and improve marketing ROI. Build Tableau dashboards, write and optimize SQL queries, conduct segmentation and lifecycle analysis, validate data quality, and provide actionable recommendations. Partner with marketing, product, and analytics stakeholders to translate business needs into analytical solutions and support strategy across channels, including spend allocation, targeting, attribution, and campaign effectiveness.

Leads marketing and sales analytics strategy, architecture, and measurement. Builds data models, pipelines, machine learning datasets, attribution and incrementality models, and revenue-performance analyses. Advises leaders on investments, tools, account prioritization, and funnel economics. Establishes data, metric, testing, and privacy standards; partners with Marketing, Sales, Finance, Revenue Operations, Data Engineering, and IT; plans roadmaps; presents recommendations to executives; and mentors analysts and engineers.

Own advanced advertising measurement strategy for Connected TV, including incrementality testing, lift studies, attribution, experimental design, and performance validation. Advise customers and internal teams on interpreting complex measurement results, lead analytical enablement, partner with engineering and measurement vendors, resolve ambiguous post-launch challenges, and translate cross-customer insights into product strategy, go-to-market materials, and scalable best practices.

Designs and delivers backend systems, APIs, data models, ETL workflows, data interactions, and user interfaces. Optimizes data operations for scalability, performance, integrity, and security while contributing to automated testing and CI/CD. Requires strong Python and Apache Spark experience, distributed computing knowledge, Agile experience, and data analysis skills. The role supports healthcare-focused digital services in a remote-first environment.

Analyzes fraud, credit, portfolio, alert, case, and customer data to identify trends, typologies, losses, control gaps, and process inefficiencies. Develops fraud KPIs and KRIs, supports detection models and rules, evaluates alert and investigation lifecycles, and delivers executive-ready reporting aligned with BSA/AML, regulatory, and audit standards. Partners with Fraud Operations, Compliance, Risk, Product, and Technology teams to improve detection, escalation, investigation, and resolution outcomes.