Top Senior Data & Analytics Jobs in Portland, ME

Leads Microsoft cloud data and AI implementations for clients, including requirements gathering, dimensional modeling, ETL pipeline development, Power BI reporting, performance tuning, data governance, and Azure DevOps delivery. Builds client relationships, mentors junior consultants, oversees project teams and source code, supports presales, and drives continuous improvement. The role is remote with travel requirements.

Leads Alteryx’s product telemetry and analytics function, including instrumentation, semantic-layer governance, self-service analytics, intake prioritization, capacity planning, and executive communication. Manages a team in India, develops talent, improves data adoption and trust, and partners with technical and business leaders to sequence platform work. The role requires expertise in product analytics, data architecture, analytics operating models, metric governance, and stakeholder enablement.

Leads enterprise data governance for federal and DoD environments, developing standards, classification and access policies, quality thresholds, retention frameworks, metadata practices, steward networks, and governance workflows. Configures Microsoft Purview controls, validates RBAC through Microsoft Entra ID, supports Master Data Management, facilitates governance boards, and reports on governance maturity.

Administer and develop a SQL Server data warehouse supporting government testing metrics. Responsibilities include ETL development with SSIS and SSDT, complex T-SQL query creation and optimization, database performance and security, backup and disaster recovery, data quality validation, database maintenance, reporting and visualization support, deployment, documentation, and process improvement.

Leads the enterprise data function, including strategy, platform modernization, analytics, data science, governance, architecture, and talent development. Oversees migration from Crystal Reports and Oracle to Databricks and Power BI, builds data connectivity and quality practices, establishes a data science function, develops internal expertise, and advises senior leadership on data-driven decisions.

Leads enterprise analytics strategy, data integration, governance, reporting, dashboards, forecasting, and advanced business analysis. Manages analysts and partners with Sales, Pricing, Finance, Product Management, Operations, and executive leadership to translate complex data into actionable recommendations. Oversees Power BI dashboards, KPI frameworks, data quality, predictive modeling, and reporting automation to improve growth, profitability, pricing, and operational performance.

Analyzes healthcare claims, clinical, administrative, and real-world data to develop and validate quality measures and certification criteria. Builds analytical datasets and pipelines using cloud platforms, performs data quality validation, and supports interoperability initiatives. Translates complex findings into recommendations, dashboards, presentations, and executive insights while partnering with clinical, product, business, and technology teams. Contributes to predictive analytics, risk stratification, benchmarking, and evidence-based healthcare quality improvement.

Leads digital customer experience insights by translating behavioral, journey, Voice of Customer, and performance data into actionable recommendations. Maps end-to-end experiences, identifies friction and drop-off, maintains experience health dashboards, and partners with product, marketing, UX, and engineering on experimentation and optimization. Communicates findings to leadership and supports customer-first product decisions through analytics, competitive benchmarking, and proactive insight delivery.

Build and own production data pipelines using Snowflake, Airflow, dbt, and Python; implement canonical data models; embed validation, quality checks, lineage, freshness, and alerting; support governed self-service data delivery; migrate workloads; partner with business consumers; participate in on-call and incident reviews; and mentor engineers while maintaining strong testing, CI/CD, documentation, and code-review practices.

Supervise actuarial predictive modeling initiatives for insurance pricing, portfolio management, and planning. Collaborate with actuaries, data scientists, underwriters, and management to develop, validate, govern, and implement models. Establish assumptions, loss adjustments, usage guardrails, monitoring practices, and model documentation. Support regulatory filings, improve team workflows, contribute to strategic projects, and mentor staff in actuarial and technical skills.