Top Senior Data & Analytics Jobs in Portland, ME

Designs and builds production data systems, pipelines, database schemas, analytical models, and internal platforms. Responsibilities include writing tested code, optimizing queries and storage, controlling infrastructure costs, enforcing CI/CD, and implementing data testing, monitoring, and alerting. The role also develops AI and LLM-backed data use cases, including retrieval pipelines, embeddings, vector storage, evaluation harnesses, and agentic workflows.

Analyzes complex datasets to uncover business insights, develops dashboards and reports using SQL and visualization tools, and presents recommendations to stakeholders. Partners with engineering, operations, and other teams to solve business problems, prioritize strategy and projects, manage deliverables, and ensure data accuracy and timeliness.

Build and maintain ETL and data pipelines using Python, PySpark, and AWS services. Orchestrate workflows, develop event-driven integrations, optimize data storage and queries, process API and JSON data, and implement data quality monitoring. Support CI/CD, production operations, cloud migration, data lake and lakehouse initiatives, and near-real-time systems while collaborating with stakeholders to deliver technical solutions.

Designs and governs PANTHERx’s semantic layer on Databricks, including Unity Catalog metric views, Gold-layer tables, promotion logic, and reusable data products. Establishes canonical, versioned business metrics for BI, analytics, partner feeds, and AI inputs. Responsibilities include data modeling, migration, validation, observability, documentation, governance, stakeholder collaboration, and mentoring analytics engineers. The role requires advanced SQL, Python, and PySpark skills, strong Databricks expertise, and experience operating across analytics engineering and data engineering.

Own Fi’s data platform and analytics roadmap, building event-driven pipelines, warehouse models, self-serve BI, and experimentation capabilities. Lead and develop a team of four analysts while partnering with Finance, Product, and Hardware on forecasting, unit economics, device analytics, retention, and board reporting. Serve as a strategic data leader in a fast-growing Series B startup.

Own and scale client-facing data transformation pipelines for financial and operational data. Build reliable analytical models, data integrity tests, and integrations across diverse sources. Partner with Customer Success and Engineering to troubleshoot data issues, optimize critical pipelines, establish engineering standards, and improve developer experience. Use dbt, SQL, Python, BigQuery, and AI-enabled workflows to deliver performant, well-documented FP&A data products while mentoring teammates and contributing to hiring and onboarding.

Design, develop, and optimize enterprise-scale data platforms, pipelines, data lakes, warehouses, and analytical datasets on Azure and Snowflake. Build ETL/ELT processes using ADF, Databricks, PySpark, SQL, Python, and Snowflake. Manage data models, governance, security, quality, CI/CD, cloud migrations, and performance optimization. Collaborate with stakeholders, troubleshoot production issues, document solutions, and support Agile delivery.

Provides remote and in-country monitoring, evaluation, accountability, and learning technical assistance across development and emergency programs. Responsibilities include designing MEAL systems, indicators, data collection tools, budgets, evaluations, dashboards, and learning agendas; supporting donor proposals; deploying to humanitarian responses; training and mentoring staff and partners; generating evidence; and engaging donors, governments, and peer organizations. Requires strong analytical, strategic, facilitation, relationship-management, and communication skills, with up to 40% travel.

Designs and builds modern data applications, pipelines, transformations, enrichment processes, provisioning layers, and interfaces supporting clinical and operational healthcare processes. Analyzes clinical data to identify trends, collaborates with Product, Platform, and Architecture teams, mentors junior data engineers, and evaluates emerging technologies. The role emphasizes cloud computing, big data, data science, modern development frameworks, source control, documentation, and repeatable engineering practices.

Lead analytical support for performance marketing by evaluating CAC, ROAS, LTV, conversion, retention, and acquisition efficiency. Conduct deep-dive analyses, experimentation, incrementality studies, and marketing measurement using SQL, Python, and visualization tools. Build scalable reporting frameworks, improve data quality, communicate insights to senior stakeholders, influence channel and budget decisions, and mentor junior analysts.