Top Remote Data & Analytics Jobs in Portland, ME

Designs, builds, tests, maintains, and optimizes large-scale data pipelines, ETL processes, ingestion workflows, and cloud data storage. Develops Databricks data engineering and AI/ML pipelines, Azure Data Lake solutions, Power BI dashboards, and CI/CD automation. Ensures data quality, security, scalability, cost efficiency, and reusable engineering practices while collaborating with distributed technical teams.

Leads enterprise business intelligence and analytics solutions using Power BI and Microsoft Fabric. Designs semantic models, certified datasets, dashboards, DAX calculations, data transformations, security controls, and governed self-service analytics. Assesses and modernizes reporting portfolios, develops predictive and forecasting capabilities, gathers requirements, validates data quality, supports documentation and adoption, and mentors analysts. Collaborates with business, engineering, governance, and security stakeholders to establish scalable enterprise analytics standards.

Leads Databricks lakehouse delivery across bronze, silver, and gold layers. Designs SAP and manufacturing data models, conformed dimensions, fact tables, governed datasets, and reusable outputs for reporting, forecasting, and AI/BI. Owns data quality, reconciliation, documentation, performance optimization, testing, and engineering delivery standards. Partners with architecture, BI, master data, product, application, and integration teams to onboard sources and deliver trusted data products.

Designs, builds, deploys, and maintains scalable data architectures, databases, ETL/ELT pipelines, API integrations, and cloud data solutions in AWS GovCloud. Migrates on-premises databases to cloud platforms, optimizes data models and performance, implements governance and security controls, and supports reporting and analytics. Collaborates with architects, data scientists, and stakeholders while documenting systems and conducting integration, validation, cost, and risk assessments.

Processes, reviews, qualifies, and quality-assures hydrographic, topographic, and bathymetric data in GIS environments. Maintains national bathymetry models, supports deconfliction and product development, improves documentation and data management, and creates or optimizes automated workflows involving hydrography, physics, and geodesy. Requires experience with geospatial data analysis, GIS software, Python programming, database management, mapping standards, and ocean and coastal data products.

Manages and evolves enterprise data lakes and warehouses, designing scalable AWS-based batch, CDC, and near-real-time ETL/ELT pipelines. Builds data quality, governance, lineage, security, monitoring, and recovery controls; optimizes Spark, Glue, Athena, Redshift, and S3 workloads. Develops reusable Python, SQL, and PySpark frameworks, supports schema evolution and analytical data modeling, and collaborates with business and technical stakeholders to deliver reliable data solutions.

Customer-facing technical leader who architects, builds, and optimizes large-scale data engineering and lakehouse solutions on Databricks. Supports pre-sales and delivery with POCs, performance/load testing, workload sizing, migrations, observability, and adoption through workshops and community engagement.

Analyzes healthcare datasets to identify trends, risks, and opportunities; develops SQL-based reports, dashboards, and data solutions using Excel and reporting tools. Supports data extraction, validation, forecasting, regulatory reporting, process improvement, and ad hoc analysis. Translates stakeholder needs into analytical requirements, presents findings, documents workflows, and collaborates cross-functionally on reporting projects.

Own the Finance and Operations data layer, integrating systems into Snowflake and Omni, building reusable data models, dashboards, governed metrics, validation checks, and reconciliation workflows. Partner with Finance, Operations, and Data teams to translate business processes into trusted analytics, improve data quality, automate reporting, and support leadership decision-making.

Analyzes healthcare claims, provider, pharmacy, and enrollment data to identify trends, improve data quality, optimize workflows, reduce costs, and support business decisions. Translates business needs into requirements, develops complex SQL queries, validates data, recommends process improvements, coordinates projects, and serves as a liaison among operations, research and development, IT, and external partners. Also mentors team members and communicates technical findings to nontechnical stakeholders.