Top Remote Data & Analytics Jobs in Pittsburgh, PA

The Staff Data Analyst will build Boulevard's product data foundation, create data-driven recommendations, develop dashboards, conduct deep analyses, and foster a data-driven culture within the organization.

Senior hands-on Cloud Data Architect responsible for designing scalable, secure Snowflake-based data platforms and lakehouse solutions, enabling enterprise analytics and AI-native applications. Lead architecture, create design artifacts and blueprints, define scope and sizing, translate business requirements into technical solutions, collaborate with security and data teams, mentor junior staff, and guide implementation.

Lead design and implementation of Snowflake-based data architectures; serve as primary Snowflake POC. Design performant Snowflake solutions (data sharing, clean rooms, virtual warehouses, micro-partitions, zero-copy clone, time travel, resource monitors, security). Tune SQL and queries. Work with data virtualization (Starburst, Denodo), Hadoop ecosystem, and build data lakes on Cloudera Data Platform. Strong written and verbal communication.

Design, build, and optimize end-to-end ETL/ELT pipelines using Python and PySpark for large structured and unstructured datasets. Ensure data quality through validation and reconciliation, troubleshoot performance issues, implement CI/CD and code review practices, and collaborate with IT and business stakeholders to translate requirements into scalable data solutions.

Lead and build Harvey’s people analytics function: design the people data architecture, consolidate HR systems, define metrics and methodology, create dashboards and forecasting models, surface leading indicators for intervention, enable self-serve analytics, and partner with People Ops, Recruiting, Finance, and Data Engineering to drive strategic workforce decisions.

Lead design, build, and maintain scalable batch and streaming data pipelines and data warehouse models. Ensure data quality, observability, performance, and security. Own workstreams, support production incidents, and enable analysts and downstream applications.

The Data Engineer will design and maintain data pipelines, optimize cloud data warehouses, and collaborate with analytics teams while mentoring junior staff.

Manage end-to-end analytics projects, lead cross-functional teams, ensure client satisfaction, and utilize AI tools to enhance data insights.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.

The Solution Engineer - Data Engineering Specialist will provide technical leadership in the financial services sector, collaborating with sales teams to demonstrate Snowflake's data platform capabilities while engaging with technical and executive stakeholders.

Design, support, and improve data analytics solutions (OAC and Power BI). Manage data ingestion, ETL, data quality, access, and documentation. Liaise with stakeholders, migrate dashboards from OAC to Power BI, and follow SDLC and project management practices.

Develop and run SAS programs to validate and clean surveillance and research data, create codebooks and data plans, perform geospatial and molecular HIV analyses in R, collaborate on novel code and reporting, and support dissemination to federal and external partners while ensuring data quality and documentation.

Develop and validate surveillance, clinical, and research datasets using SAS and R. Identify and resolve data discrepancies, create codebooks and data management plans, perform geospatial and molecular HIV analyses, collaborate on code development, and support dissemination and reporting to federal and external partners.

Partner with clinical and operations leaders to build scalable real-time reporting, measure team performance and SLAs, perform root-cause analyses, advance data modeling and best practices, and enable stakeholder self-service using BI and AI capabilities.