Top Remote Data & Analytics Jobs in Cleveland, OH

Build and support production analytics models using SQL, dbt, BigQuery, Looker, and LookML. Develop governed semantic layers, self-service analytics, automated tests, and reliable datasets for business and AI use cases. Partner with stakeholders to translate ambiguous requirements into reusable solutions, investigate data discrepancies, optimize performance, support platform modernization, and maintain data quality, privacy, and documentation.

Leads enterprise advanced analytics and modeling to identify drivers of business performance across brands, markets, customers, accounts, and geographies. Translates findings into prioritized actions, playbooks, launch strategies, and scenario-based recommendations. Oversees rigorous, scalable analytical approaches, partners with senior stakeholders, and develops analytics talent across the organization.

Builds business-critical dashboards, scorecards, reports, and ad hoc analyses using SQL, Python, Excel, Power BI, and Tableau. Analyzes KPIs, identifies trends and root causes, automates recurring reporting, validates data, and translates complex findings into actionable insights for stakeholders and leadership. The role collaborates with data engineers and cross-functional teams to improve reporting workflows, data pipelines, and decision-making.

Own the architecture and standards for a trustworthy BI analytics platform. Design data models, ingestion and transformation patterns, lineage, PII controls, reliability SLAs, observability, schema governance, and cost management. Partner with engineers, analysts, business leaders, Security, Legal, and Compliance; enforce testing, CI/CD, infrastructure as code, and data quality practices. Mentor data professionals and document architectural decisions.

Supports regulatory reporting by defining data requirements, developing repeatable data flows, performing data cleansing and analysis, monitoring data quality, troubleshooting reporting issues, and creating reports, templates, documentation, and quality controls. Collaborates with actuarial data teams and business process owners to improve reporting scalability, accuracy, and compliance.

Owns end-to-end customer analytics workstreams, including KPI frameworks, multi-source dashboards, reporting, data governance, quality assurance, and insight delivery for government digital communications programs. Presents recommendations to stakeholders, mentors junior analysts, leads Agile ceremonies, documents analytics practices, resolves data issues, and evaluates AI-assisted analytics tools.

Leads the integration workstream for an Informatica SaaS MDM implementation. Designs, develops, tests, deploys, and supports batch, real-time, API-based, and event-driven integrations across enterprise systems. Establishes architecture and development standards, manages source-to-target mappings and reconciliation, troubleshoots production pipelines, and ensures governance compliance. Mentors offshore developers, conducts code reviews, and collaborates with business, MDM, data quality, and source-system teams throughout project delivery.

Owns Hagerty’s Qualtrics experience-management platform, including survey programming, contact-list management, deployments, dashboards, and feedback outputs. Analyzes research and survey data to identify themes, develops reports and narratives, presents insights to stakeholders, and supports project timelines and communications. The role also coordinates with internal teams, maintains People Insights resources, and recommends improvements to research and reporting processes.

Designs, builds, operates, and modernizes secure ETL/ELT data pipelines for public health interoperability. Responsibilities include using NiFi, Kafka, Python, and SQL; deploying pipelines on Azure or AWS; implementing CI/CD with GitHub Actions; monitoring with Grafana; troubleshooting production systems; supporting legacy migrations; and ensuring data security, compliance, scalability, and reliability. The role collaborates with architects, integration engineers, data scientists, DevOps/SRE, and product teams.

Designs, develops, and maintains scalable cloud-based data pipelines and enterprise data solutions. The role covers data ingestion, transformation, orchestration, integration, data lakes, cloud warehouses, batch and streaming processes, performance optimization, governance, and lineage. The Senior Data Engineer collaborates with analysts, data scientists, engineers, stakeholders, contractors, and vendors while mentoring junior staff. Core tools include Databricks, dbt, Azure Data Factory, SQL, Python, and Azure.