Top Senior Analysis Reporting Jobs in Portland, ME

The Senior Manager of Data Insights will lead a team to optimize data sharing and governance, develop data strategies, and deliver actionable business intelligence across Docker's operations.

As a Senior Data Scientist, you will guide data-driven decision-making, lead experimentation, and collaborate on actionable insights to enhance product strategy and metrics.

As a Senior Data Analyst, you'll define analytics strategies, implement data infrastructure, perform analyses, and leverage AI to enhance decision-making across the organization, focusing on personalized coaching outcomes.

The M365 Power Platform Specialist will design and implement automation solutions using Microsoft tools to enhance workflows and optimize business processes while collaborating with stakeholders to deliver tailored solutions.

The Senior Data Engineer will design and implement lakehouse architectures, optimize ClickHouse deployments, develop ETL/ELT pipelines, and create data models to support analytical and operational functions.

The Lead Implementation Specialist is responsible for data integration, reporting, and visualization, ensuring compliance, facilitating client support, mentoring, and driving continuous improvement in data processes.

Lead design and delivery of large-scale data pipelines and warehouse systems. Define technical strategy, enforce data governance, improve developer efficiency, mentor engineers, and align data engineering efforts with business goals to enable analytics and ML at scale.

Design, optimize, and scale Snowflake-based data architecture and pipelines. Implement data observability, operationalize MLOps, build semantic enterprise models, and deploy AI-assisted agents and automation for production analytics and commercial data products. Share cross-functional ownership for pipeline resilience, monitoring, and model lifecycle management.

Own slide-grade analytics for PE and executive audiences by transforming Salesforce and BI outputs into polished board packs, causal commentary, reusable templates, and executive narratives. Attribute pipeline variance, produce funnel and revenue analytics, train client teams, and ensure deliverables are modular, PE-ready, and maintainable across engagements.

Lead analytics engineering: design scalable dimensional models, build modular tested transformations, replace brittle pipelines with reusable patterns, drive semantic layers and self-service analytics, partner on data architecture, and provide cross-functional technical leadership and governance.