Top Data & Analytics Jobs in Buffalo, NY

Lead analytics engineering: architect, build, and maintain scalable data pipelines and dbt models; ensure data is research-ready; partner with Engineering, Data Science, and Commercial teams; implement product analytics and optimize data workflows for scale.

Own strategy, governance, and operations for GTM data in Salesforce. Lead data enrichment, vendor management, data movement architecture, observability, quality standards, deduplication, and lifecycle policies. Provide user support, analyze issues with SQL/SOQL, and coordinate with Data Engineering and GTM teams to ensure CRM is single source of truth.

Design and implement credit strategies using data, machine learning, A/B testing and advanced analytics to optimize underwriting, pricing, and credit line decisions. Lead end-to-end analytics for credit card products, monitor portfolio performance, conduct root-cause analysis, partner cross-functionally, and communicate findings to stakeholders.

Lead enterprise Power BI architecture and governance, design scalable semantic models and high-performance reports, enable self-service analytics, optimize large-dataset performance, and mentor analytics teams while aligning solutions with business requirements and data engineering.

Optimize publisher monetization by analyzing bidstream and auction data, building monitoring/alerting systems, running A/B tests, performing root-cause analyses, and producing actionable insights for cross-functional teams to maximize yield and revenue.

The Data Analyst will perform advanced data modeling and analysis, manage data collection systems, and communicate findings to stakeholders, driving data-informed business decisions.

Own lightweight data governance and operational reporting: define/document business terms, maintain a data catalog, build SQL-based operational datasets and reports, monitor data quality, diagnose anomalies, and align stakeholders across BizTech, Analytics, and business teams.

Build and maintain cloud data pipelines and ML feature/model workflows in Snowflake and AWS. Implement data ingestion, transformations, quality checks, monitoring, and documentation. Collaborate with data scientists, analysts, and product teams to support analytics, audience insights, rapid prototyping, and reliable production deployments.

The Senior Analytics Engineer will design and build scalable data pipelines using dbt and Snowflake, providing technical guidance, conducting audits, and mentoring junior engineers while leveraging AI tools to enhance productivity.

Design, develop, and optimize Tableau dashboards and data sources on Redshift; collaborate with data engineering (dbt) and business teams; own Tableau governance, performance tuning, documentation, training, and ensure data security compliance.