Top Remote Data & Analytics Jobs in Buffalo, NY

Develop and maintain automated ETL solutions using SSIS, Oracle SQL, and PL/SQL to move data between Oracle and SQL Server systems. Design database, data warehouse, and ETL interfaces; analyze requirements; establish development, documentation, and testing standards; manage change deployments; and monitor project schedules. Collaborate with stakeholders, assess database changes and downstream impacts, document solutions, communicate issues, and mentor junior staff.

Deliver and interpret catastrophe modelling and exposure analytics across global insurance portfolios. Support accumulation monitoring, PML optimization, exposure data quality, reinsurance treaty analysis, portfolio reporting, and strategic risk decisions. Collaborate with underwriting, exposure data, ceded reinsurance, brokers, reinsurers, capital providers, and model vendors. Improve and automate catastrophe modelling, exposure management, and reporting workflows while translating complex results into actionable insights.

Leads audience research, advertising effectiveness, brand lift studies, and first-party audience analysis. Partners with Sales, Creative Strategy, Media Planning, and leadership to develop actionable insights, sales narratives, measurement strategies, presentations, and client recommendations. Manages research vendors, budgets, contracts, and methodologies while scaling research tools, dashboards, benchmarks, and best practices across the organization.

Build and scale the data backbone for HR, payroll, finance, and insurance products. Design data models across warehouses and data lakes, develop and optimize batch and real-time ETL/ELT pipelines, improve data quality and governance, tune SQL queries, address data integration gaps, and collaborate with engineering, BI, analytics, and business stakeholders.

Lead a Salesforce data engineering team to design, deliver, and support Salesforce-to-Salesforce integrations and migrations, data modeling, ETL/transformations, automation, and observability. Manage hiring, performance, and career development; partner with stakeholders; adopt AI/LLM agent tooling to automate workflows and improve data quality; reduce technical debt and document systems and processes.

Builds and maintains scalable data pipelines and cloud infrastructure supporting an AI biomedical research platform. Responsibilities include ingesting, harmonizing, validating, and documenting multimodal neurodegeneration datasets; managing cloud storage, compute, permissions, and costs; implementing de-identification and data governance workflows; supporting research data repositories and AI/ML teams; and maintaining data lineage, catalogs, and technical documentation. The role requires strong Python and SQL skills, software engineering discipline, cloud experience, and neurodegeneration research data expertise.

Design and architect robust ETL/data pipelines on cloud platforms. Build and automate data ingestion and preprocessing using Spark/Databricks, AWS Glue, Airflow. Implement warehousing architectures (EDW, DM, ODS, MOLAP/ROLAP), ensure SQL-based data quality, use version control, and deliver tested production pipelines while communicating with stakeholders.

Build and maintain product analytics dashboards, validate and QA event tracking, translate event data into analytics-ready datasets, run funnels/cohorts/retention analyses, support A/B testing, and surface actionable product insights to Product, Growth, and Data stakeholders.

Design, build, and maintain data pipelines, dashboards, and predictive models. Analyze large datasets to generate actionable insights, collaborate with stakeholders, ensure data quality and governance, and document/share analytics best practices to support Marketing, Product, Operations, and Workforce teams.

Build and maintain data infrastructure, integrate veterinary partner systems, develop dbt models and pipelines, provide analytics modeling, testing, reporting, and deliver actionable insights to customers and internal teams.