Top Remote Data & Analytics Jobs in Boston, MA

Develop and govern financial data solutions for Liberty Mutual’s Finance Data Platform. Analyze source data, define transformation and downstream reporting requirements, apply metadata, lineage, security, and compliance principles, and build proof-of-concept solutions using coding and financial data expertise. Collaborate with business and technology stakeholders, define impactful metrics, enable self-service data consumption, mentor junior associates, prioritize Agile work, and identify Gen AI applications for data discovery and documentation.

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.

Define and lead enterprise data governance: create standards, operating model, and AI-ready data practices. Partner with data product managers, platform engineering, security, legal and privacy to enable self-service, metadata, lineage, quality, access controls, and compliance while building governance councils and driving adoption.

Supports enterprise data management and analytics initiatives through SQL and ETL development, data quality monitoring, metadata and master data management, data integration, dataset analysis, and governance practices. Collaborates with stakeholders and cross-functional teams, troubleshoots data integrity issues, develops dashboards and insights, and presents project outcomes. The internship is hybrid in Columbus, Johnston, or Boston and requires permanent U.S. work authorization.

Ten-week hybrid summer internship supporting data and analytics initiatives across banking teams. Interns will gather requirements, assemble and explore structured and unstructured data, perform analysis, identify trends, create insights and dashboards, collaborate with business partners, communicate findings, and present a capstone project. Assignments may include advanced analytics, reporting, visualization, data mining, automation, root-cause analysis, cohort analysis, and model development.

Graduate data analytics interns support data gathering, cleaning, exploration, analysis, reporting, dashboarding, visualization, and business insight initiatives. They collaborate with mentors and cross-functional teams, investigate trends, communicate findings to stakeholders, refine analytical approaches, and present project outcomes. The 10-week hybrid program is based in Columbus, Johnston, or Boston.

Build and support scalable data platforms and pipelines, leading migrations such as Snowflake to BigQuery and transitioning reporting to Looker. Responsibilities include data architecture, ETL/ELT, API and marketing integrations, data quality, production troubleshooting, warehousing, performance optimization, and platform modernization. The role partners with analytics and business teams, owns projects through production, documents solutions, and provides technical guidance.

Analyze and transform cloud data using SQL, dbt, and Google Cloud; build automated pipelines, data visualizations, validation checks, unit tests, monitoring, and alerts. Partner with engineering teams and enterprise insurance clients to improve data quality, governance, automation, and decision-making. Communicate insights clearly, document technical work, develop insurance domain expertise, and contribute to collaborative reviews and on-call support.

Designs, develops, and supports analytics data solutions for clients, including Snowflake and dbt ingestion and transformation pipelines, data marts, validation, monitoring, governance, and documentation. Manages multiple consulting projects, budgets, timelines, quality assurance, troubleshooting, client communication, and implementation planning. Requires strong data engineering experience, regulated-industry knowledge, stakeholder communication, and willingness to travel.

Lead complex data analyses, develop statistical models, write advanced SQL, build data models and dashboards, and establish technical standards for analytics. Mentor analysts, troubleshoot data quality and modeling challenges, partner with data engineering, translate ambiguous business questions into rigorous analyses, and communicate findings to senior stakeholders. Own the analytics function’s technical roadmap while ensuring data privacy and security practices.

Administer and enhance Edmunds’ Databricks data platform and AWS infrastructure. Build and maintain ETL pipelines, infrastructure-as-code tooling using Terraform or CDK, and operational dashboards, alerts, and reports. Collaborate with business, engineering, analytics, security, and infrastructure teams to support data platform users and AI solutions. Evaluate new technologies, troubleshoot platform issues, and improve operational, cost, and security visibility.

Build scalable, secure data pipelines, models, platforms, and governance systems that enable AI applications to access trusted enterprise data. Partner with analytics, marketing, and product teams to translate requirements into technical solutions, independently deliver projects through production, and support sensitive-data security and access controls. Preferred experience includes LLM architectures, cloud data platforms, infrastructure as code, regulated environments, and technical leadership.