Top Data & Analytics Jobs in Portland, ME

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.

Supports the Transformation Office through enterprise KPI reporting, performance analysis, executive dashboards, governance materials, and strategic insights. The role identifies risks and opportunities, validates initiative updates, tracks decisions and action items, and prepares executive, board, and investor-ready reporting. It partners with Finance and senior leaders to connect transformation progress with business outcomes and uses Power BI to develop dashboards.

Supports commercial loan system administration, department reporting, and analysis of deposit and lending activities. Works with large datasets across multiple systems to synthesize actionable insights, collaborates with credit union departments, and performs related administrative and analytical tasks under supervision. The internship is fully remote with optional office work and is limited to 29 hours per week.

Leads the design, development, and implementation of advanced Power BI business intelligence solutions. Builds reports, dashboards, semantic models, and data transformations using Power Query and DAX; analyzes complex datasets; applies AI and analytics technologies; provides technical leadership, governance, stakeholder guidance, and mentoring across multiple projects.

Leads end-to-end healthcare payer data conversions between platforms, including profiling, transformation mapping, ETL design, mock and parallel runs, bulk loading, validation, testing, defect resolution, documentation, and client reporting. Develops Python and SQL conversion routines, manages risks and timelines, collaborates with onshore and offshore teams, and mentors junior staff. Requires expertise in claims, enrollment, or provider data and extensive technology integration leadership.

Build and maintain scalable ETL/ELT pipelines, integrate travel and customer data from internal and external systems, develop cloud data warehouse models, implement data quality monitoring, support real-time streaming, and ensure data privacy and regulatory compliance. Collaborate with analysts, data scientists, and product teams to deliver reliable datasets for personalization, forecasting, pricing, route optimization, and customer experience initiatives.

Develop and deploy business intelligence applications for a U.S. Air Force financial platform across development, testing, integration, and production environments. Design and optimize Informatica ETL pipelines, Oracle databases, SQL and PL/SQL processes, data warehouses, BI semantic layers, and SAP integrations. Support Agile delivery, budgeting integrations, monitoring, interface changes, and security hardening. The role also requires Oracle APEX, WebLogic, HTTP Server, performance tuning, and collaboration on data-related issues.

Develop and support enterprise business intelligence solutions by aggregating data, analyzing data sources, and building Tableau dashboards, reports, and SQL queries. Partner with stakeholders to translate business needs into technical solutions, document data domains, support data modeling and governance, and collaborate with Reporting, Analytics, and Data Engineering teams. The role requires healthcare data warehousing experience, strong SQL Server BI skills, stakeholder support, and compliance with privacy and security requirements.

Leads causal inference studies, clinical outcomes analysis, member insights, and strategic opportunity sizing. Translates ambiguous business questions into analytical approaches, applies statistics and machine learning, establishes analytics best practices, mentors analytics professionals, and presents recommendations to executive leadership. Requires healthcare payer data expertise, advanced quantitative methods, strong SQL and Python skills, and experience with cloud data platforms and scalable analytical datasets.

Lead development and delivery of enterprise risk adjustment analytics and BI solutions. Translate clinical, claims, and operational data into actionable provider and market-level insights, drive KPI reporting, modernize analytics via AI/automation, oversee BI platform strategy, and lead a team to support stakeholders across Risk Adjustment, Finance, Clinical, and IT.

Conduct quantitative and qualitative research, analyze complex business scenarios, gather requirements, and synthesize stakeholder perspectives into actionable recommendations. Evaluate data using tools such as Excel or SQL, identify process improvements, and produce clear reports, memos, business cases, and documentation. Collaborate with stakeholders through written communication and contribute analytical content to help train AI systems.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Design, build, and maintain scalable big data pipelines, architectures, distributed databases, and storage systems. Use Python and frameworks such as Hadoop, Spark, or Flink for data integration, transformation, and processing. Ensure system performance, availability, security, governance, and data quality while collaborating with cross-functional teams and documenting technical solutions.