Top Remote Analysis Reporting Jobs in Baltimore, MD

Own end-to-end data architecture, including ingestion, ETL, transformation, extracts, reporting, and dashboards. Lead DevOps and infrastructure for AI engineering systems, establish platform standards, and build reliable production infrastructure. Write and ship code, mentor engineers, and hire and lead a growing data and platform team. Partner with leadership to align architecture and platform investments with product, research, and business priorities.

Designs, builds, and operates scalable batch and streaming data pipelines, ELT/ETL workflows, and cloud data infrastructure. Ensures data reliability, quality, observability, lineage, performance, and cost efficiency across enterprise domains. Partners with analytics engineers, BI teams, and business stakeholders to deliver analytics-ready datasets. Establishes engineering practices including version control, CI/CD, automated testing, infrastructure-as-code, architecture standards, and documentation.

Leads the full digital experience research lifecycle, including user interviews, testing, surveys, behavioral analysis, experimentation, and conversion optimization. Defines research and web measurement strategies, analyzes qualitative and quantitative data, builds dashboards and executive presentations, and translates findings into compelling data stories. Partners with marketing, technology, design, product, and development teams to improve global web experiences, while maintaining scalable research documentation and insight repositories.

Develops and maintains Power BI dashboards and data models, defines KPIs with stakeholders, validates data accuracy, and collaborates with Data Engineering on optimized analytical models. The role documents data lineage and reporting assumptions, supports self-service BI through communications and training, and automates manual reporting processes. It requires SQL, Power BI, DAX, Power Query, data modeling, and data warehouse knowledge, plus strong communication and cross-functional collaboration skills.

Lead design, build, and operate scalable Databricks/Delta Lake data pipelines and Kimball dimensional models using dbt. Manage governance with Unity Catalog, optimize performance and cost, operationalize ML with MLflow, and coordinate/quality-check offshore vendor engineering. Mentor engineers, uphold standards, and deliver trusted data products that power analytics, reporting, and MLOps workflows.

Support marketing analytics by analyzing digital channel performance, building and maintaining KPI dashboards, ensuring data accuracy, and collaborating with cross-functional teams to turn insights into actionable recommendations.

Design, build, and scale data pipelines, ETL workflows, analytics infrastructure, and machine-learning data systems. Ensure data quality, security, monitoring, and reliability while optimizing storage and processing performance. Collaborate with engineering, product, and analytics teams on data requirements, modeling, schemas, and scalable infrastructure. The role also establishes data engineering best practices and supports a data-driven culture.

Leads enterprise business intelligence and analytics across multiple divisions and locations. Establishes governed KPI definitions, reporting architecture, financial and operational analytics, semantic models, data-quality practices, and self-service reporting. Partners with FP&A, IT, Finance, and Operations to align analytics with financial results, guide technical delivery, evaluate BI platforms, and support forecasting and performance improvement. Directs internal or external development teams and communicates actionable insights to executives and operating leaders.

Analyze clinical data completeness, reliability, and effectiveness across healthcare facilities, vendors, interoperability networks, and integration pathways. Reconcile claims with clinical records, identify missingness and latency, report ADT coverage, evaluate data technologies, recommend vendor configurations, and prioritize facilities for direct acquisition. Partner with product, engineering, and clinical teams to improve scalable, trustworthy data pipelines and support TEFCA and QHIN strategy.

Leads customer data engineering strategy, delivery, team development, and roadmapping. Oversees data-driven product improvements, digital programs, quality initiatives, budgets, cybersecurity remediation, and portfolio management. Manages, mentors, and grows data engineering teams, including contractor teams, while guiding customer data platforms, omnichannel identity resolution, complex data modeling, and personalization-focused data science capabilities. Partners across the organization to execute strategic initiatives and build team capability.