Top Remote Data & Analytics Jobs in Rochester, NY

Designs and leads enterprise data pipelines and integrations across Snowflake, Oracle Fusion, on-premises databases, and cloud applications. Ensures data quality, governance, security, scalability, and performance while supporting Power BI, AI/ML, and self-service analytics. Partners with business and technical stakeholders, leads migrations, mentors engineers, optimizes data platforms, and establishes engineering best practices.

Designs, builds, deploys, and maintains scalable data pipelines, data lake systems, batch and streaming processing, MLOps frameworks, data documentation tooling, and an agentic data exploration platform. The role supports customer-facing products and enables engineering teams through reliable infrastructure, observability, data discovery, and AI capabilities.

Leads CookUnity’s Advanced Analytics function, setting strategy and partnering with Product, Finance, Operations, Marketing, and leadership. The role involves experimentation, causal inference, retention and growth analysis, marketing measurement, product impact evaluation, and translating insights into business decisions. This hands-on player-coach will guide complex analytical work, develop analysts, improve analytical rigor, and shape team structure and priorities.

Supports Somali-speaking learners in a fully virtual data analytics program. Responsibilities include answering questions, facilitating breakout rooms, holding office hours, reviewing materials, grading assignments, providing feedback, recording walkthroughs, monitoring learner progress, and escalating concerns. The role also requires supporting live sessions, communicating in Somali and English, attending onboarding and staff meetings, and submitting weekly progress reports.

Owns the enterprise Snowflake data platform end to end, including architecture, ingestion, transformation, security, governance, reliability, performance, cost optimization, and AI enablement. Establishes engineering standards, reviews architecture, resolves complex production issues, mentors data professionals, and leads cross-functional adoption of scalable, governed analytics capabilities. The role provides senior technical influence without direct people management and supports secure MCP-based AI integrations.

Supports ADL’s Center on Extremism law enforcement and audit teams by maintaining a law enforcement database, preparing reports, reviewing incidents, cleaning data, and analyzing trends. The intern will help improve data quality, inform research and reporting, collaborate with subject matter experts, and present work internally.

Own analytics for Root’s Customer Experience domain and policyholder retention. Develop metrics, analytical frameworks, experimentation systems, and strategic recommendations. Partner cross-functionally with Product, Engineering, Data Science, and Operations to shape roadmaps, evaluate customer initiatives, quantify business impact, and influence senior leadership decisions through rigorous analysis and clear communication.

Leads and manages an analytics engineering team while contributing to data transformation, modeling, quality, and delivery solutions. Establishes modeling and development standards, implements analytics engineering tools, supports client engagements, improves reporting and visualization processes, allocates team resources, mentors engineers, supports presales, and drives internal quality and process improvements.

Analyzes business and operational needs, gathers requirements, evaluates data and systems, and recommends technology solutions. Develops advanced SQL queries, reports, system models, and process improvements. Responsibilities include troubleshooting, data architecture integration, software and hardware solution design, database analysis, automation using scheduling or RPA tools, and project leadership. Senior levels guide other analysts and assess technology’s business impact.

Design and implement enterprise data architectures supporting batch and real-time analytics, ETL/ELT, data warehouses, streaming pipelines, CDC, and cloud data platforms. Build AI-ready data infrastructure for RAG, vector search, and Generative AI applications. The role requires production experience with Treasure Data/CDP, Kafka, Snowflake or Databricks, cloud services, and modern AI data engineering technologies.