Top Tech Jobs & Startup Jobs in Boston, MA

Leads healthcare consulting engagements focused on financial, clinical, and operational improvement for hospitals and provider organizations. Performs data and business process analysis, develops recommendations, manages project deliverables, coordinates teams, presents results to executives, and supports proposals and business development. Uses Excel, Tableau, Power BI, and other tools to analyze large datasets, benchmark performance, identify savings opportunities, and improve operational processes.

Leads financial management transformation initiatives for defense and national security clients. Responsibilities include modernizing financial processes, implementing Power Platform solutions, developing dashboards and performance metrics, assessing business processes, recommending improvements, managing project plans, presenting to senior stakeholders, and supporting automation, analytics, visualization, and AI capabilities. The role also ensures alignment with federal financial policies, audit readiness, and operational standards.

Own end-to-end production data platforms, writing Python and SQL, designing AWS pipelines, modeling analytics data, and implementing quality and reconciliation controls. Make architecture decisions independently, ensure correctness and auditability, and use AI coding tools effectively. The role also supports applied AI initiatives including entity resolution, LLM-assisted analytics, embeddings, and anomaly scoring.

Develop AI and machine learning solutions for fraud, anomaly detection, semantic search, entity resolution, and investigative analytics. Build and operationalize models across structured and unstructured data using AWS data lakehouse services, generative AI, NLP, graph analytics, and document intelligence. Evaluate model performance, explainability, monitoring, and risk scoring while supporting production integration, dashboards, and investigative workflows. Collaborate with technical teams, investigators, stakeholders, and federal clients in an Agile environment.

Administer, secure, optimize, and modernize enterprise Oracle and cloud database platforms in a federal hybrid-cloud environment. Responsibilities include production database maintenance, performance tuning, backup and recovery, high availability, incident response, automation, infrastructure-as-code, migrations, vulnerability remediation, documentation, and cross-functional troubleshooting. The role supports Oracle, Azure, Tessell, and additional database technologies while maintaining reliable 24x7 operations and contributing to DevSecOps and continuous improvement initiatives.

Designs, develops, and implements Microsoft Power Platform solutions across discovery, build, testing, and deployment. The role gathers client requirements, creates Canvas and Model-driven Power Apps, automates processes, integrates data, develops visualizations, and supports governance. Responsibilities also include technical documentation, end-user training, quality assurance, scrum participation, client presentations, and maintaining knowledge of Power Platform updates. The position requires at least three years of Power Platform or Dynamics 365 CRM experience and up to 25% travel.

Analyzes data and builds analytical datasets, data models, SQL queries, Python notebooks, dashboards, and reports using Databricks and BI tools. Identifies trends, validates data quality, translates business requirements into reporting solutions, documents data logic, and communicates insights to technical and non-technical stakeholders. The role also supports governance, security, lineage, and compliance across collaborative client delivery projects.

Design and implement enterprise Databricks architectures supporting data engineering, analytics, AI/ML, and governed data products. Administer workspaces, Unity Catalog, compute, security, automation, and platform operations. Translate business and security requirements into technical designs, governance standards, deployment patterns, and operational playbooks. Partner with cloud, cybersecurity, identity, networking, and DevOps teams across Azure, AWS, and GCP. Lead architecture reviews, troubleshoot platform issues, advise clients, and support secure, scalable production deployments.

Develop, train, evaluate, deploy, and monitor machine learning and statistical models using Databricks, Python, SQL, Spark, Delta Lake, and MLflow. Prepare datasets, engineer features, manage model lifecycles, validate data, and support governance practices. Translate client requirements into scalable analytics solutions, analyze trends, and communicate findings to technical and non-technical stakeholders while collaborating across data science, engineering, cloud, security, and business teams.

Design, build, and maintain scalable batch and streaming data pipelines using Databricks, PySpark, Python, SQL, Spark, and Delta Lake. Develop transformations, orchestration workflows, data models, validation processes, and curated data products. Troubleshoot performance and quality issues, apply governance and security practices, document solutions, and collaborate with architects, data scientists, DevOps teams, analysts, and clients.