Top Remote Data & Analytics Jobs in Boston, MA

Analyzes business performance, trends, competitor filings, and product-line data for personal lines property and specialty insurance. Develops advanced queries and analytical tools, conducts state and countrywide reviews, manages projects and workstreams, and recommends strategic and tactical improvements to products, pricing, technology, and business initiatives. Presents findings to product managers and serves as a subject matter expert on assigned states and products.

Build and operate production data pipelines supporting analytics, AI, and agentic workflows. Responsibilities include implementing canonical data models, maintaining Databricks or Snowflake platforms, monitoring reliability, responding to incidents, validating healthcare data mappings, improving performance and cost, and documenting architecture. Requires strong SQL and Python skills, cloud data platform experience, ETL/ELT orchestration expertise, and healthcare or pharmaceutical data experience.

Develops and maintains Salesforce and Tableau analytics dashboards, performs complex data analysis and forecasting, and delivers insights for sales, product, finance, and marketing decisions. Translates business needs into technical requirements, manages platform enhancements with developers, validates data quality, models sales goals, identifies optimization opportunities, and presents strategic recommendations. Provides user training and supports analytics across Treasury Solutions.

Leads complex private banking data management and analytics initiatives, defining data strategies, quality standards, product attributes, and integrated client views. Partners with business, engineering, analytics, AI, and Wealth teams to translate needs into dashboards, KPIs, predictive models, personalized insights, and intelligent decision-making capabilities. Serves as a subject matter expert on private banking products while mentoring junior team members and enabling platform readiness.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

Build and own end-to-end data products, including pipelines, transformations, semantic models, dashboards, metrics, and AI-enabled workflows. Partner with business and technical stakeholders to turn ambiguous questions into trusted, maintainable solutions. Establish data quality testing, documentation, monitoring, and governance while improving architecture and automation. Use Snowflake, dbt, Power BI, and related technologies to support analytics across Marketing, Product, Finance, and Engineering.

Architect scalable data models and ELT pipelines using modern data lake technologies. Build self-service analytics products, establish enterprise data governance and observability standards, and lead data architecture across engineering teams. Partner with data scientists, product engineers, and business stakeholders to improve data literacy, identify root causes, and connect insights to business outcomes. Develop AI-enabled data tools and frameworks while providing technical leadership, mentorship, and direction for analytics engineering practices.

Own enterprise reporting strategy and Sigma BI platform administration, governance, security, and development. Partner with business and analytics teams to define KPIs, build scalable data models and reporting frameworks, and enable root-cause analysis and self-service reporting. Lead Sigma adoption through training, documentation, and best practices. Collaborate on analytics engineering initiatives involving Databricks, dbt, data pipelines, AI, and machine learning while connecting data insights to business outcomes.

Design and maintain analytical data models, transformation frameworks, data-quality checks, semantic definitions, and metric consistency across analytics and customer-facing products. Partner with engineering, product, and analytics teams to document data, improve lineage, and enable trustworthy self-service data usage. The role requires advanced SQL, analytics engineering, dimensional modeling, testing, and collaborative translation of business concepts into precise data definitions.

Lead the architecture, development, and scaling of data pipelines and infrastructure for a customer-facing Data Lake platform. Build ETL and ingestion systems using GCP, Debezium, Pub/Sub, Dataflow, BigQuery, Python, Golang, and SQL. Establish engineering standards, deliver strategic projects, mentor engineers, influence cross-functional technical decisions, optimize data services, and shape the platform roadmap.

Lead the architecture and development of Vercel’s next-generation data platform, supporting batch and real-time integrations, analytics, data warehousing, and AI/ML workloads. Design scalable systems using Kafka, ClickHouse, Tinybird, and Snowflake; establish data governance and security standards; guide architectural decisions and roadmaps; collaborate with engineering, product, security, compliance, and leadership teams; write production code; and mentor engineers.

Leads the enterprise data platform strategy, architecture, governance, and evolution. Manages a central data team and enables federated self-service analytics across business functions. Builds AI-ready data pipelines, RAG and Graph RAG architectures, custom data applications, observability, cost optimization, and AIOps capabilities. Requires hands-on expertise with Snowflake, dbt, modern ETL, Python, SQL, CI/CD, and Data Mesh architectures, along with 5+ years leading technical data teams.