Top Senior Data & Analytics Jobs in Portland, ME

Lead analytics for member engagement and revenue recognition: build and validate Braze attributes, run attribution and A/B test analyses, maintain Looker dashboards, join campaign and engagement data via SQL/DBT, and provide actionable recommendations to Member Operations and Marketing.

Lead and grow a data engineering team, set technical standards and roadmap, architect scalable GCP data solutions (ingest, transform, warehouse, serving), ensure pipeline reliability and data quality, partner with analytics and client teams, drive best practices (CI/CD, IaC, governance), and evaluate new tooling.

Design, deploy, and govern enterprise-scale data architectures and platforms to support analytics and AI. Define modeling standards, integration pipelines, data quality, lineage, and security. Lead technical direction, mentor engineers, evaluate AI tooling, and support proofs of concept and solution roadmaps that enable generative AI and RAG solutions.

Develop and optimize T-SQL scripts to transform legacy SIS data for loading into the Jenzabar platform, manage multiple conversion projects, communicate with clients and internal teams, adhere to project plans and timelines, estimate custom work, and improve conversion processes.

Lead a team to design, build, and maintain cloud data engineering solutions using Microsoft Fabric and Azure Synapse. Responsibilities include architecture, data pipelines, lakehouse and warehousing implementation, governance, performance optimization, mentoring engineers, cross-functional collaboration, support/on-call, documentation, and ensuring reliability and compliance.

Lead creation and publication of data-driven economic research using Life360 first‑party and external data. Develop seasonal adjustment frameworks, craft public narratives, serve as company spokesperson, partner with Data & Analytics, Product, and Comms, and build data‑storytelling methodology within compute and time-series constraints.

The professor will develop and teach courses in computer and data science, advance a research agenda, and engage in departmental collaboration and meetings.

Build, operate, and modernize scalable data pipelines and warehouse environments for lottery reporting, analytics, and AI readiness. Improve ingestion, transformations, data models, contracts, observability, lineage, and onboarding patterns. Automate operations, troubleshoot production issues, mentor engineers, and support migration from legacy to cloud architectures while ensuring data quality, reliability, and regulatory continuity.

Lead capacity planning and commercial analytics: build and maintain capacity reporting, dashboards, and NetSuite inventory processes; enforce data governance and KPIs; partner with Sales, Finance, and Operations to enable data-driven commercial decisions and scalable growth.

Lead development and governance of the supply chain data warehouse and analytics platforms. Build SQL-driven models, dashboards, and KPIs to drive inventory optimization, cost reduction, supplier performance, and working capital improvements. Support ERP integrations and data migrations, perform deep data discovery and predictive analytics, and present actionable insights to senior leaders to enable strategic decision-making.