Top Analysis Reporting Jobs in Buffalo, NY

Develops data infrastructure, analytics solutions, prototypes, and enterprise data assets supporting data science and predictive modeling. Collaborates with data scientists, engineers, and business partners to define requirements, build and test solutions, support user acceptance, and deliver rapid data engineering work tracks. Uses SQL, Python, and Spark for agile data analysis and parallel processing. Also contributes to proof-of-concept designs, documentation, process improvement, and team mentoring.

Own the analytical function for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate insights; and drive recommendations through execution. The role requires strong first-principles thinking, independent data work, persuasive communication, stakeholder influence, and ownership of ambiguous, high-impact initiatives.

Designs and maintains scalable data pipelines, warehouse models, and analytics solutions. Builds natural-language data interfaces using GenAI and LLM techniques, optimizes SQL, improves data quality and observability, and supports distributed data platforms on AWS or GCP. Partners with engineering, analytics, business, and product teams, contributes to shared codebases, establishes development standards, and participates in production on-call and incident response.

Manages data management program implementation across business units, including training, working groups, policy compliance, metadata capture, data quality monitoring, risk indicators, and issue remediation. Analyzes large datasets for business insights, promotes business intelligence adoption, coordinates cross-functional stakeholders, and supports regulatory, audit, and internal control requirements.

Maintains Looker and LookML dashboards, explores, and reporting infrastructure; supports ad hoc analysis, forecasting, sales pacing, data quality, UAT, vendor management, board reporting, and planning materials during a temporary maternity-leave backfill.

Owns automated dashboards, SQL-based analysis, data pipeline monitoring, exploratory analysis, and executive recommendations. The role tracks marketplace KPIs such as customer lifetime value, acquisition costs, churn, and provider utilization while partnering with engineering and product teams on data requirements. It is fully remote within the United States and requires advanced SQL, dashboard development, and strong analytical communication.

Leads data engineering, business intelligence, and analytics teams; oversees data pipelines, integration infrastructure, database architecture, CI/CD practices, and enterprise data platform strategy. Partners with business and technology stakeholders to define requirements, improve data capabilities, maintain Ubuntu-based services, and deliver reporting and KPIs to leadership. Responsible for team hiring, development, mentoring, operational health, and technical execution across analytics and data integration platforms.

Forecasts contact volume, capacity, and staffing for a virtual healthcare clinic. Monitors real-time queues, adherence, service levels, and intraday risks; combines multiple data sources to create staffing recommendations and reporting. Uses AI and LLM tools to test and improve forecasts, while accounting for clinician licensing constraints. Requires contact center WFM experience, strong Excel skills, analytical communication, and comfort working remotely with required equipment and connectivity.

Build and scale business intelligence solutions that automate processes, integrate and transform data, and deliver actionable visualizations. Partner with business stakeholders to define requirements, develop Databricks workflows and pipelines using SQL and PySpark, collaborate with technology and data science teams, lead project deliverables, and mentor junior team members.

Manage the health, performance, reliability, and cost of customer Snowflake and Databricks environments. Responsibilities include customer onboarding, account and warehouse setup, permissions, data ingestion, query optimization, cost reporting, incident response, escalation support, and automation using Python and Terraform. The role also advises customers and internal teams on data platform best practices and participates in on-call rotations.