Top Analysis Reporting 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.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Plans, designs, creates, maintains, and troubleshoots departmental databases and reporting tools. Conducts research, data analysis, testing, and data-flow reviews; coordinates information exchange with vendors and business partners; supports automation, hardware, and application implementations; and recommends improvements to data quality, timelines, security, and reporting. Presents insights to diverse audiences, quantifies business risk, and collaborates with technology and business teams to address information needs.

Leads growth analytics strategy and a multidisciplinary technical team spanning data science, engineering, business intelligence, and marketing analytics operations. Owns marketing-to-sales measurement, attribution, funnel intelligence, data strategy, MarTech integrations, AI-enabled analytics, and revenue optimization. Partners with marketing, sales, finance, and go-to-market leaders to improve demand generation, pipeline conversion, and sales outcomes while guiding technical standards, team development, vendor relationships, and analytics delivery.

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.

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.

Build and own Snowflake data models and dbt pipelines for a Customer Data Platform supporting marketing segmentation and customer journeys. Integrate complex source systems, manage data architecture and governance, conduct data discovery, and translate business rules into scalable solutions. Collaborate with engineering, analytics, product, and business stakeholders; lead technical workshops; mentor junior engineers; and implement automated data quality testing, CI/CD workflows, and AI-augmented engineering practices.

Own the Databricks enterprise data warehouse and BI solution, designing data models, ETL/ELT pipelines, stored procedures, semantic layers, and governed analytics. Lead healthcare data initiatives supporting value-based care metrics such as HCC, HEDIS, Stars, utilization, MLR, and capitation. Serve as BI product owner, manage roadmap and agile delivery, enforce data quality and HIPAA-aligned controls, and lead a small team while remaining hands-on.

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.

Analyze mobile app activation, feature adoption, onboarding, engagement, retention, funnels, cohorts, and A/B tests. Build SQL and dbt models, dashboards, and self-service reports using BigQuery and GCP. Partner with product and engineering teams on instrumentation, identify data issues, automate reporting with AI tools, and communicate actionable insights to nontechnical stakeholders.