Top Analysis Reporting Jobs in Portland, ME

Manage end-to-end analytics projects, lead cross-functional teams, ensure client satisfaction, and utilize AI tools to enhance data insights.

Lead end-to-end customer engagements to architect, implement, and optimize large-scale Spark/Databricks workloads. Troubleshoot and tune PySpark and DBSQL jobs, design PoCs and workshops, advocate strategically for customers, collaborate cross-functionally, and mentor junior engineers on Lakehouse best practices.

Analyze customer and caregiver data to identify workflow improvements, build dashboards and visualizations, support Customer Success with QBRs and presentations, translate findings into actionable recommendations, and create scalable data processes while advising Product and Engineering.

Lead architecture, implementation, and optimization of scalable data platforms, ETL/ELT pipelines, and data governance. Ensure security and compliance, mentor junior engineers, drive CI/CD and IaC for data workflows, and collaborate with stakeholders to deliver actionable analytics and reporting.

Design, build, and maintain scalable distributed data pipelines and a secure data lakehouse for streaming and batch processing to support real-time analytics, ML, and experimentation. Automate, test, and harden workflows, architect logical and physical data models, build ML model features, and collaborate with product, analytics, and data science teams to turn data into value.

Build and operate ingestion and transformation pipelines, model and test core warehouse data, enable analytics and reporting, and maintain ML data infrastructure feeding matching and recommendation models. Partner with Engineering, Product, and Data Science to ensure reliable, documented, and trusted data at scale.

The Databricks Architect leads data engineering solutions, designing scalable Databricks platforms and managing cloud implementations. They work with clients, ensuring technical alignment and project execution.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

Analyze commercial data for sales, marketing, service and support to create metrics and insights for optimization. Collaborate with cross-functional teams to provide data-driven recommendations and manage business intelligence tools.

Design, develop, and manage data infrastructure for internal and client projects, focusing on large-scale data pipelines, APIs, and cloud deployments.