Top Data & Analytics Jobs in Buffalo, NY

The Senior Data Engineer will design and scale cloud-based data platforms, ensuring quality and performance while collaborating with cross-functional teams to deliver actionable data solutions.

Lead study design, survey development, questionnaire quality, data analysis, and client-ready reporting for financial services research. Interpret findings with client teams, translate results into actionable business insights, apply analytical methods, and ensure accuracy, clarity, timeliness, and integrity across multiple projects.

Leads complex, enterprise-scale data engineering initiatives using Databricks and Azure. Designs and implements scalable lakehouse architectures, high-performance pipelines, and platform capabilities while establishing engineering standards for reliability, security, observability, and cost efficiency. Mentors engineers, leads through influence, embeds across teams to accelerate delivery, manages technical risks, and advises stakeholders on data strategies and architectural trade-offs. Collaborates with Architecture, Platform, AI, Analytics, Security, and Governance teams.

Profiles and analyzes data sources, documents end-to-end lineage, maps source data to canonical models, and supports API schema design. Develops data quality, validation, metadata, and governance documentation while collaborating with engineers, architects, clients, and stakeholders to define clear technical requirements for enterprise data products, APIs, and analytics.

Lead-level analyst who designs, develops, and delivers reports, dashboards, and data solutions (SQL, Power BI, SSRS, Excel). Analyzes complex healthcare, financial, and operational data, ensures data quality and ETL processes, mentors analysts, manages analytics projects, drives automation and process improvements, and presents insights to leadership and stakeholders.

Design, operate, and scale end-to-end data infrastructure and pipelines. Build reusable data models and a semantic layer, ensure data quality and privacy, implement observability and SLAs, support marketing and growth feeds, partner with cross-functional stakeholders, and enable ML/AI consumption and reverse ETL workflows.

Designs and maintains healthcare data pipelines, ETL workflows, databases, data models, and analytical frameworks. Analyzes claims and payer data to identify trends and insights, while ensuring data quality and integrity. Creates reports, dashboards, and visualizations for nontechnical stakeholders and collaborates with healthcare policy experts, analysts, and other stakeholders to translate requirements into data solutions. The role also improves data infrastructure and analytics capabilities.

Build and maintain scalable data pipelines, warehouse models, metrics, and data quality systems for Airbnb’s AirCover programs. Reconcile external partner data, publish analytics-ready datasets, improve pipeline observability and reliability, and collaborate with engineering, product, finance, operations, analytics, and data science stakeholders. Contribute to data engineering standards and foundational systems supporting reporting, experimentation, claims operations, financial reconciliation, and expansion into new markets.

The Lead, Advanced Analytics, Acquisition will analyze data, define metrics, conduct A/B tests, and collaborate with teams to drive growth and insights.

Support an insurance actuarial department by cataloging and classifying data, maintaining master data mappings and schemas, auditing data quality, enforcing governance policies, and ensuring regulatory compliance. Collaborate with technical and business stakeholders, conduct Alation and Excel training, and lead data governance projects aligned with organizational objectives.

Lead Business Analyst for Payment Integrity responsible for analyzing client data, capturing business requirements, designing product solutions, supporting bids, documenting processes, driving implementations, and delivering KPI-driven insights. Works cross-functionally with sales, marketing, finance, and delivery to build business cases and improve claims auditing and analytics outcomes.

Lead and manage a remote Data Engineering team to build scalable data pipelines and lakehouse solutions. Own execution of Medallion architecture using Databricks, Boomi/Rivery, dbt, Delta Lake and SQL Server; implement DataOps, CI/CD, observability, and stakeholder intake while growing engineers and improving team maturity.