Top Data & Analytics Jobs in Buffalo, NY

Implement and maintain Informatica data governance solutions, including metadata management, data quality, lineage, and stewardship workflows. Develop automated ingestion, transformation, and validation processes; integrate Snowflake with Informatica and cloud platforms; monitor pipeline reliability; document governance standards; support reporting; troubleshoot data issues; and provide technical guidance to business and technical teams.

Analyze data and build analytical datasets, data models, dashboards, reports, and visualizations using Databricks, SQL, Python, and BI tools. Translate business requirements into reporting solutions, validate data quality, identify insights, document analytical logic, and support governance, security, lineage, and compliance. Collaborate with engineers, data scientists, architects, clients, and other stakeholders to deliver accurate, secure, and well-documented analytics solutions.

Build, test, and maintain batch and event-driven data pipelines and ETL/ELT workflows. Transform and validate large datasets, troubleshoot data-quality issues, improve workflow reliability, and support platform modernization. Collaborate with engineering, product, and data stakeholders while following strong practices for version control, testing, monitoring, documentation, and code review. The role may occasionally require work outside standard business hours.

Design and implement attribution, source tracking, CRM integrations, ROI measurement, funnel reporting, and sales performance systems for B2B clients. Consult with revenue leaders, define metrics, build and validate reporting across marketing, sales, CRM, advertising, and BI platforms, troubleshoot data quality issues, document solutions, and train client teams. Contribute to implementation methodologies, technical content, automation, and AI-enabled data validation and analysis.

Design, build, and optimize scalable data pipelines using Databricks, PySpark, SQL, Delta Lake, and lakehouse architecture. Collaborate with analytics, product, and engineering teams while developing batch and streaming workflows, integrating data warehouse systems, and using cloud platforms and orchestration tools such as Azure, Airflow, ADF, or Prefect.

Lead analytics and data science initiatives to drive measurable business outcomes across various functions, including Underwriting and Claims. Oversee the full analytics lifecycle, foster stakeholder engagement, and mentor junior team members.

Reviews and annotates video content by identifying objects, people, actions, events, and visual details for AI training. Follows project guidelines, checks annotation quality, corrects inconsistencies, flags unclear content, meets productivity targets, and adapts to updated requirements. The role requires independent, detail-focused work, strong written English comprehension, basic computer skills, reliable internet, and personally provided equipment suitable for video annotation.

Own EULER’s data lifecycle, including instrumentation, validation, reconciliation, privacy, anonymization, canonical data modeling, analytics datasets, documentation, and production pipelines. The role requires strong SQL, software engineering practices, independent ownership, skepticism toward data quality, and clear communication. Preferred experience includes GDPR/LGPD, multi-tenant B2B SaaS, dbt, statistics, Cloudflare Workers, Postgres, Parquet, DuckDB, and Bubble.

Analyzes healthcare datasets, including claims, pharmacy, utilization, and cost data, to develop reports, dashboards, forecasts, and actionable insights. Builds and maintains SQL-based reporting and data processes, validates data quality, supports regulatory reporting, and identifies automation and process improvements. Partners with stakeholders to define requirements, presents recommendations, supports projects and audits, and provides guidance to other analysts.

Designs, develops, tests, and maintains scalable public health data pipelines, enterprise data marts, and cloud-based informatics systems. Uses Databricks, SQL, Python, PySpark, and related technologies to integrate, transform, curate, and govern multisource data. Performs data quality assurance, monitoring, troubleshooting, documentation, and dashboard development while collaborating with clinical, technical, public health, and external partners to improve interoperability, surveillance systems, and data-driven decision-making.