Top Remote Entry Level Data & Analytics Jobs in Boston, MA

Collect, clean, validate, and analyze operational data from multiple systems to support customer reporting and performance monitoring. Process SQL-based uploads, maintain accurate datasets, identify trends and anomalies, document reporting procedures, and create standardized workflows, dashboards, and tools. The role also supports process improvement and automation initiatives while collaborating with cross-functional teams and traveling to customer sites.

Maintains and verifies client and matter data across business intake and conflicts systems. Processes engagement, waiver, closure, and name-change requests; links parties; maintains ethical walls, database alerts, and administrative files; performs data cleanup and reporting projects; supports technology testing; and communicates intake and risk-management procedures to attorneys, staff, and external parties.

Build and maintain scalable data pipelines, infrastructure, data models, and APIs using Python, SQL, Airflow, Snowflake, dbt, Terraform, and cloud services. Ensure data quality, security, observability, and reliability while collaborating with analysts, product managers, and engineering teams. Own aspects of the FastAPI data service, including design, deployment, monitoring, and performance. Handle sensitive healthcare data in compliance with governance standards.

Leads a data engineering team and supervises one Data Engineer while designing, maintaining, and optimizing reliable data pipelines and infrastructure. The role integrates internal and external data sources, supports SaaS analytics dashboards and connected platforms, improves data-store performance, and ensures infrastructure quality, security, and uptime. Requires proficiency in Python, databases, distributed processing, orchestration, AWS, and machine learning.

Supports order-to-cash data integrity and physical fulfillment operations by improving processes, controls, data quality, automation, and reporting. The role collaborates with Business Systems, Finance, Supply Chain, and fulfillment teams on system implementations, audits, risk mitigation, KPI dashboards, and continuous improvement initiatives. It also documents best practices, monitors SLAs and KPIs, and advises leadership on process and technology improvements.

Conducts research and outreach to collect official local election documents, processes election and candidate data, and maintains Ballotpedia’s database. Monitors election schedules, audits and cleans data, interprets election materials, researches election laws, and improves workflows and local election coverage. The role requires careful, organized, neutral research, collaboration, concise communication, and effective use of online productivity tools in a fully remote environment.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Leads hands-on big data processing, data engineering, and analytics workflows using Azure Databricks, Python, and SQL. Develops insights and reporting with Power BI, Tableau, and Excel. Analyzes complex datasets, communicates findings to business stakeholders, manages competing priorities, meets deadlines, and promotes continuous improvement.

Analyzes and prepares customer data for successful migration to ServiceTitan. Works directly with customers to understand source databases, identify data issues, interpret database structures, and map data to ServiceTitan’s model. Writes queries to correct, reformat, and transfer data while coordinating with engineers, implementation teams, and onboarders. Manages shifting priorities, deadlines, project updates, and cross-functional communication to ensure accurate, timely data delivery.

Early-career Data Engineering Analyst supporting AIG’s Data Office through a rotational program. Responsibilities include developing cloud-based data pipelines, collecting and transforming data, building modern software systems, and supporting analytics and data science use cases. The role emphasizes data quality, security, compliance, collaboration, analytical problem-solving, and professional development through mentoring, masterclasses, and on-the-job experiences.