Top Senior Data & Analytics Jobs in Portland, ME

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

The Senior Business Management Analyst develops Power BI dashboards, executive presentations, and recurring reports supporting insider risk, sales practices, and team productivity monitoring. The role analyzes trends, case and employee data, monitoring effectiveness, and anomalies; prepares data lineage and process documentation; supports monitoring scenario development; and advises management on risks, opportunities, and operational improvements. It also coordinates initiatives across business areas and communicates findings to leadership.

Designs and delivers end-to-end enterprise data solutions on a GCP-native platform, covering ingestion, transformation, modeling, security, quality, and analytics consumption. Defines data mappings, dimensional models, and platform patterns; selects GCP services; guides engineers; reviews implementations; and translates business requirements into executable designs. The role also produces architecture documentation, supports modernization and EDW migration, collaborates across technical and business teams, and contributes to AI-ready data products and Agile delivery practices.

Leads enterprise Data and AI platform governance, operations, adoption, optimization, security, and compliance. Manages analytics strategy and team performance while overseeing data pipelines, predictive models, analytical databases, and workflows. Partners with technical and business stakeholders to translate needs into solutions, improve platform value, establish standards, and support responsible innovation. Responsibilities include recruiting, coaching, mentoring, cost optimization, vendor management, and communicating complex technical findings to diverse audiences.

Lead and develop a team of data engineers while contributing hands-on to design, implement, and operate scalable, secure data pipelines. Partner with product, software, and architecture teams to deliver cloud-native data solutions, ensure production reliability, and drive engineering best practices and continuous improvement.

Leads quantitative and qualitative market research on international development, AI adoption, institutional demand, funding, procurement, competition, and commercial opportunities. Evaluates AI and data service applications, develops market assessments and strategic recommendations, manages research initiatives, prepares executive presentations, and collaborates with leadership, technical, operational, and business development teams to support market entry and growth.

Build and guide data platform capabilities supporting marketing, finance, analytics, and data science. Develop data collection, integration, scoring, experimentation, analytics, and infrastructure solutions; contribute code, lead cross-functional technical initiatives, improve system resiliency through incident response, and establish engineering standards. Partner with business and technical stakeholders to define strategy and long-term roadmaps.

Lead financial data engineering initiatives involving commissions, incentive programs, and backend financial systems. Build scalable, accurate, and reliable data pipelines, platform tooling, partner integrations, analytics infrastructure, and data science infrastructure. Shape technical strategy and roadmaps, collaborate with Finance, Product, Data Science, and Engineering, mentor engineers, contribute code, lead incident response, and establish engineering standards.

Owns DeVry University's website measurement ecosystem, including GA4, GTM instrumentation, event taxonomies, data quality, tracking governance, and conversion measurement. Analyzes SEO, AI search visibility, website journeys, acquisition, engagement, and conversion performance using SQL and dashboarding tools. Investigates anomalies and friction, supports experimentation, automates monitoring, and delivers prioritized recommendations. Partners with web, marketing, SEO, technology, analytics, and external teams to improve measurement reliability, digital experience, and prospective student conversion.

Build and support production analytics models using SQL, dbt, BigQuery, Looker, and LookML. Develop governed semantic layers, self-service analytics, automated tests, and reliable datasets for business and AI use cases. Partner with stakeholders to translate ambiguous requirements into reusable solutions, investigate data discrepancies, optimize performance, support platform modernization, and maintain data quality, privacy, and documentation.

Leads enterprise advanced analytics and modeling to identify drivers of business performance across brands, markets, customers, accounts, and geographies. Translates findings into prioritized actions, playbooks, launch strategies, and scenario-based recommendations. Oversees rigorous, scalable analytical approaches, partners with senior stakeholders, and develops analytics talent across the organization.