Top Tech Jobs & Startup Jobs in Boston, MA

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

Remote coordinator who schedules insurance appraisal appointments, supports homeowners with a photo-capture self-survey app, updates work order statuses, meets productivity targets, and communicates with managers, underwriters, agents, and policyholders to resolve issues and maintain quality.

Design, build, and operate production-grade, event-driven data pipelines (Kafka/Flink) on GCP to deliver model-ready features. Optimize BigQuery SQL and Parquet performance, develop Python data workloads (Polars/Pandas), deploy ML pipeline components on Kubeflow/Vertex AI with Docker, design event store architectures, and collaborate with ML and platform teams while documenting architecture and standards.

Design and implement AWS-based data architectures and lakehouse solutions, lead data engineering teams, build ETL and real-time pipelines (Kafka/Kinesis), use DBT and Airbyte for ingestion and transformation, orchestrate workflows with Airflow/MWAA, enforce security/compliance, and guide infra automation with Terraform/CloudFormation and CI/CD.

Lead design and build scalable autonomous and semi‑autonomous multi‑agent AI systems. Implement RAG pipelines, tool‑calling agents, memory, observability, and AgentOps. Ensure production readiness, safety, governance, and secure data handling. Provide technical leadership, mentor engineers, and shape platform standards across teams.

Lead Data Engineer builds and maintains scalable data pipelines and lakehouse/warehouse platforms (Databricks) to support analytics, BI, reporting, and AI. Responsibilities include data modeling, ETL/ELT, medallion architecture, orchestration and monitoring (Airflow/Cron), performance tuning, CDC/incremental loads, data quality, and leading/mentoring a team while collaborating with stakeholders and maintaining documentation.

Lead end-to-end data engineering on GCP: design scalable data platforms and architectures (lake/lakehouse/warehouse), build and optimize BigQuery/Spark pipelines, ensure data quality/security, enable ML workflows with Data Science, mentor engineers, and own delivery and performance.

Lead design and implementation of credit card products across onboarding, account management, lifecycle, and customer communications. Maintain PRDs, define backend data needs, coordinate integrations with support and controls, enable launches with legal/compliance, and support prioritization, product build activities, and cross-functional alignment.

Develop and deploy statistical and machine learning models to analyze customer behavior across marketing and digital channels. Design and evaluate experiments/A-B tests, apply causal inference, build scalable Python/SQL pipelines, query Redshift, use SageMaker for production models, maintain version-controlled workflows, and present insights to cross-functional stakeholders.

Lead agentic delivery and large-scale data migration/modernisation programs, institutionalise DataOps and CI/CD, design multi-agent workflows for SDLC acceleration, ensure security and responsible AI controls, and manage large cross-functional agile teams and client engagements.