Top Senior Analysis Reporting Jobs in Portland, ME

As a Senior Data Engineer, you'll transform raw data into datasets, design production pipelines, integrate customer data, and collaborate with various teams to ensure data quality and reliability.

As a Senior Data Analyst, you will analyze game telemetry data, translate business needs into insights, and guide technical teams. You will also lead exploratory data analysis and maintain data quality practices.

The Manager, RCM Strategy & Analytics oversees analytics and insights for Revenue Cycle Management, collaborating to improve performance through data interpretation and visualization.

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.