Top Senior Analysis Reporting Jobs in Portland, ME

As a Senior Data Engineer, you will enhance the data lakehouse, optimize data workloads, perform complex transformations, and develop frameworks to improve delivery velocity, focusing on cybersecurity solutions.

The role involves managing actuarial modeling for Retirement Plans, ensuring quality of outputs, overseeing BAU execution, and training junior staff.

Analyze revenue and growth performance, provide insights on auction behavior, measure A/B tests, define KPIs, and perform root-cause analysis.

Lead global partner analytics and planning for partner GTM motions. Build dashboards, business models, AI-enabled workflows, and executive reports to support partner planning, incentives, coverage, performance management, and cross-functional decision-making across hyperscalers, ISVs, marketplaces, and reseller channels.

Lead data-focused business analysis: elicit and document requirements, model data and processes (As-Is/To-Be), design data flows, support integrations, migrations, EDW/reporting decisions, mentor team members, and drive data governance and cataloguing across enterprise systems.

Design, build, and scale reliable batch and real-time data pipelines and warehouses. Partner with engineering, data science, and business teams to define data models, improve observability, optimize storage and querying, and evangelize data engineering best practices across the company.

Design, build, and maintain scalable batch and streaming data pipelines and analytics-ready data models. Implement cloud (primarily AWS) data platform solutions, data ingestion, transformation, orchestration, and observability. Embed data quality, governance, security, and metadata/lineage practices. Partner with architecture, analytics, and application teams to enable self-service analytics, reporting, and downstream use cases while driving platform evolution and engineering best practices (CI/CD, testing, documentation).

Design, build, and maintain scalable, fault-tolerant streaming data architectures and real-time pipelines using Kafka, MSK, and Kinesis. Implement stream processing, monitoring, security, IaC, and CI/CD. Collaborate with data teams, provide technical leadership, and optimize latency, throughput, and cost for real-time analytics and downstream systems.

Lead data engineering for a healthcare scheduling platform rebuild: map legacy multi-TB schema, design target schema, build translation layer (views/materialized views and write mappers), ensure data consistency during parallel systems, plan per-tenant cutover with verification and rollback, tune DB performance, instrument data quality/lineage/audit, and mentor engineers.

Lead a team to analyze sales data, build and maintain Power BI and Excel reporting, leverage AI and automation for pipeline and lead scoring, align cross-functional GTM strategies, ensure data quality, and deliver actionable, executive-ready insights to drive sales performance and quota attainment.