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

Design and maintain large-scale ETL/ELT data pipelines using Python, Airflow, Spark, and Flink. Process and transform massive datasets, develop data models for analytics and dashboards, automate workflows in Unix/Linux environments, and debug distributed systems. Collaborate with cross-functional teams to ensure data accuracy, reliability, scalability, and availability across Akamai’s global network.

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.

Designs, develops, and maintains scalable cloud-based data solutions, ELT/ETL pipelines, data warehouses, curated datasets, and transformation logic using Snowflake and related tools. Optimizes SQL and warehouse performance, monitors workflows, supports data governance and quality initiatives, documents data flows, and delivers trusted datasets for Tableau reporting. Collaborates with business and technical stakeholders in Agile processes while ensuring secure handling of sensitive PHI data.

Create and validate complex datasets for AI benchmark tasks, including files with malformed records, missing data, truncations, and inconsistent formatting. Define correct final states, write detailed grading rubrics, and assess AI outputs for accuracy and completeness. The role requires exceptional attention to detail, error detection, format reconciliation, accurate documentation, and clear asynchronous communication in regulated or audit-sensitive contexts.

Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

Develop and evaluate realistic Excel tasks and solutions for AI training data. Apply advanced Excel capabilities including formulas, PivotTables, data modeling, dashboards, Power Query, Power Pivot, and VBA across multiple industries and business functions. Provide written feedback, close research knowledge gaps, improve model performance, and collaborate with subject matter experts. Requires reliable weekday availability, initially 40 hours per week and 20 hours thereafter.

Analyze and manipulate large datasets supporting energy modeling and SEM programs. Review data before and after modeling, maintain standardized templates and databases, integrate data into statistical software, quality-control models and reports, and create work instructions. The role also involves automating data processing, troubleshooting Visual Basic and Excel tools, managing Smartsheet data, supporting benchmarking reports, and collaborating with internal teams and occasional clients.

Analyzes data sources and information management systems to identify root causes of data governance issues. Partners with data owners, clients, vendors, and data architects to resolve issues, establish governance standards, define data requirements, and integrate governance testing into ETL processes. Develops audit baselines, governance metrics, reports, policies, and continuous improvement initiatives while communicating governance benefits to stakeholders.

Organise and curate large amounts of raw material: extract key points from transcripts, collate and maintain clean spreadsheets, tag and categorise links and documents, and create findable information structures following or suggesting systems.

Own production data ingestion pipelines for healthcare and benefits data, including normalization, mapping, validation, reconciliation, observability, and secure handling of sensitive information. Unify census data processes, scale the platform, improve identity matching, and build automation and TypeScript tooling. The role requires strong Python and SQL skills, production orchestration experience, reliable testing and data-quality practices, and effective communication with technical and nontechnical stakeholders.