Top Analysis Reporting Jobs in Portland, ME

Lead reporting and application-integration architecture across Power BI, PBIRS, Power BI Embedded, and Crystal Reports. Build and optimize paginated reports, SQL queries, and stored procedures; troubleshoot app-to-report integrations; support Python data tooling; automate report delivery; implement monitoring, quality checks, anomaly detection, SLAs, and performance benchmarking.

Design and maintain scalable dbt data models and ELT pipelines in Snowflake. Architect data foundations to power AI and LLM-enabled workflows, operationalize core SaaS metrics, and build reusable data assets for analytics and activation. Partner cross-functionally to embed analytics into workflows and ensure scalable, secure architecture.

Design and maintain scalable dbt data models and ELT pipelines in Snowflake; architect reusable data assets, governance, and SaaS metrics; build AI-enabled data foundations and LLM workflows; integrate analytics into operational tools and partner cross-functionally to productionize AI-driven use cases.

Develop and maintain scalable Snowflake data warehouses, ETL/ELT pipelines, data models, and integrations across cloud and on-premises sources. Optimize queries, clustering, partitioning, and warehouse performance; implement transformations using SQL, stored procedures, and Snowpark. Monitor data quality, governance, security, deployments, and production issues. Collaborate with engineers, architects, analysts, and business stakeholders while automating workflows and contributing to data architecture and best practices.

Build, maintain, and support production data pipelines and platform capabilities using Snowflake, dbt, Airflow or Cloud Composer, APIs, files, and cloud services. Responsibilities include ETL/ELT development, data modeling, testing, deployment, monitoring, troubleshooting, optimization, documentation, and data quality. The role partners with analytics, data science, finance, risk, marketing, product, and engineering teams, while supporting reliable, scalable, and cost-effective data systems and emerging AI data workflows.

Design, build, and maintain data lakes, data warehouses, and end-to-end data pipelines for a multi-tenant SaaS platform. Lead code and design reviews, write infrastructure-as-code, optimize performance and scalability, participate in data governance, mentor junior engineers, evaluate new technologies, automate tests, collaborate cross-functionally, and join on-call rotation to ensure reliable data delivery.

Designs and maintains BI solutions, writes optimized SQL and stored procedures, and builds AI-assisted reports and dashboards using Power BI, Tableau, and Excel. Translates business questions into actionable insights for Sales and cross-functional teams, develops data models, supports reporting migrations, and ensures data quality, governance, documentation, and consistency across platforms.

Own analytics implementation and data integration for B2B ecommerce clients. Build GA4 and Google Tag Manager implementations, marketing pixels, conversion APIs, product feeds, BigQuery data models, and Looker Studio dashboards. Reconcile analytics, advertising, ecommerce, and ERP data; audit tracking issues; support CRO and experimentation; and translate findings into actionable recommendations for clients and leadership. Collaborate with developers, marketers, merchandisers, and other stakeholders while maintaining accurate, privacy-compliant measurement.

Lead partner analytics by building scalable dashboards, forecasting and ROI models, and experimental designs to evaluate and optimize partner performance. Collaborate with Product, BD, Marketing, and Data Engineering to improve pipelines, translate insights into recommendations, and mentor analysts to scale partner growth.

Design and optimize enterprise data architectures and pipelines using SQL, Spark/PySpark, Python, Apache Iceberg, AWS, ClickHouse, and PostgreSQL. Build greenfield application and data solutions, optimize databases and Spark jobs, integrate data virtualization and governance tools, and support CI/CD and infrastructure-as-code practices. Experience with financial services workloads is valued, while telecommunications knowledge is preferred but not required.