Top Analysis Reporting Jobs in Baltimore, MD

Develops business intelligence, reporting, data pipelines, dashboards, and geospatial solutions for complex real estate portfolios. Transforms and integrates data from multiple sources, builds scalable analytics products, automates reporting processes, and supports portfolio planning, occupancy strategy, workplace initiatives, and operational decision-making. Partners with stakeholders and clients to translate business needs into technical solutions, communicate insights, train users, and improve analytics adoption. The role also supports geospatial capabilities and leverages emerging AI-enabled tools.

Own and evolve end-to-end data pipeline architecture across ingestion, transformation, modeling, and serving. Lead platform improvements for cost efficiency, reliability, access control, observability, orchestration, CI/CD, and developer experience. Drive complex cross-team initiatives, resolve production issues, influence architectural decisions, mentor engineers, and build automation incorporating AI into data engineering workflows.

Supports database integration and maintenance, analyzes workflows and complex datasets, and develops, tests, deploys, and documents reports, dashboards, data exports, and communications. The role validates and interprets data, tracks KPIs and ROI, identifies trends, recommends improvements, and collaborates across the organization to meet reporting and business requirements.

Build and operate a governed Snowflake enterprise data warehouse, including ingestion, orchestration, dbt transformations, infrastructure as code, security controls, reliability checks, and CI/CD. Partner with data owners and BI teams during migration from legacy systems, ensure compliance for sensitive financial data, support reconciliation and incident resolution, and mentor engineers. The role requires hands-on ownership of pipelines and platform components across development and production environments.

Own pharmaceutical media performance reporting, analyze marketing data, develop dashboards, identify optimization opportunities, and present actionable insights to clients. Support attribution, test and control analyses, predictive modeling, AI-enhanced reporting, and process improvements. Collaborate with strategy, analytics, media, client services, data science, and technology teams to advance reporting capabilities and data-driven decision-making.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Build and maintain ETL/ELT pipelines, ingest and transform structured and unstructured data, integrate APIs and external sources, improve data quality and monitoring, support dashboards and ML pipelines, optimize warehouse and cloud performance, and contribute to data governance and documentation.

Lead and manage a remote analytics engineering team responsible for Extend’s Snowflake warehouse, dbt repository, ingestion pipelines, data models, monitoring, and quality standards. Oversee hiring and development, architecture, platform migrations, reliability, incident response, documentation, and self-service analytics. Partner with actuarial, risk, fraud, product, finance, and operations teams to establish trusted shared data definitions and prioritize platform improvements.

Administer enterprise SQL Server and Oracle databases, ensuring availability, performance, security, backup and disaster recovery. Design and maintain databases, clusters, governance documentation, reporting services, connectivity, and high-availability platforms. Perform capacity planning, monitoring, troubleshooting, patching, configuration, data integrity, and recovery testing. Coordinate with stakeholders on technical requirements, staffing, costs, long-term database planning, and continuity operations across multiple locations.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

Lead enterprise Microsoft Fabric data architecture, landing-zone design, governance, security, integration, semantic modeling, DevOps, and AI-ready platform delivery. Design scalable Lakehouse and Warehouse solutions, establish standards and operating models, guide Power BI and data engineering practices, automate deployments, and provide technical leadership across architecture reviews, discovery workshops, and implementation. The role requires deep Azure, Fabric, data engineering, security, and enterprise integration expertise.