Top Remote Data & Analytics Jobs in Rochester, NY

Lead the technical roadmap and hands-on development of a scalable data platform, build analytics and data access solutions, ensure data quality/governance/observability, mentor and grow a team of data engineers, collaborate cross-functionally, and evaluate new big-data technologies.

Entefy seeks a Senior Data Scientist with a Master's or PhD in a relevant field, and 3+ years of experience. Responsibilities include delivering advanced analytics, leading teams, and extracting insights from datasets.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

Lead reporting and analysis across product, call center, and marketing; manage enrollment and revenue reconciliation; produce partner and carrier reports; analyze member engagement and plan performance to surface actionable insights.

Design, develop, maintain, and optimize ADABAS database structures and data solutions. Support mainframe data processing (Natural, COBOL, JCL), perform migrations to modern platforms, tune performance, ensure data integrity/security, troubleshoot issues, and collaborate with developers, architects, and analysts on modernization, API/cloud integration, and data warehousing initiatives.

Build and maintain Power BI reporting products, integrate and validate institutional data, conduct applied quantitative and qualitative research, deliver analyses and visualizations, manage projects and reporting standards, and support cross-organization analytics and stakeholder decision-making.

Investigate financial transactions to identify potential money laundering activities, utilize AI for analysis, document findings, and collaborate with product teams on improvements.

As a Senior Data Analyst, you will analyze game telemetry data, translate business needs into insights, and guide technical teams. You will also lead exploratory data analysis and maintain data quality practices.

Design, build, and maintain scalable, secure data architectures, models, and ETL pipelines. Integrate diverse data sources, optimize performance and data quality, implement governance, monitor production SLAs, and collaborate with data scientists, analysts, and product teams. Provide technical leadership, documentation, and training to improve engineering practices across the organization.

Lead development of cloud data platforms and end-to-end data pipelines using AWS/Snowflake and big-data technologies (Spark, Hive, Iceberg). Automate builds and deployments with Bash/Python shell scripting, apply CI/CD and Medallion Architecture, perform data modeling and warehousing, and collaborate across teams. Pharma/AbbVie experience preferred.