Top Analysis Reporting Jobs in Baltimore, MD

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.

Develops Power BI dashboards, reports, queries, and ad-hoc analyses for supply chain operations and strategic decisions. Translates business needs and integrated data into actionable visualizations, enhances data integration and maturity, and identifies root causes through descriptive and prescriptive analytics. Collaborates with business, technology, analysts, and data scientists on agile product development, supports innovation, and helps junior team members succeed.

Develop Power BI dashboards, reports, and queries that translate complex supply chain data into business solutions. Partner with operations and technology teams to prioritize analytics requests, perform ad hoc analysis, identify root causes, and support strategic decisions. Use Azure Data Lake, SQL, ETL tools, and agile methodologies to improve data integration and maturity while collaborating with analysts, data scientists, and business stakeholders.

Lead account-level analytics strategy by translating client objectives, media performance, and cross-channel data into measurement plans, testing roadmaps, dashboards, and actionable recommendations. The role requires client-facing data storytelling, BI and SQL proficiency, quantitative analysis, quality control, and collaboration with media and strategy teams to improve marketing decisions and measurement effectiveness.

Organize and curate large volumes of raw information: extract key points from transcripts, maintain clean spreadsheets, curate links/resources, tag and categorize content, and follow or propose systems for information structure. Part-time remote role with initial 10 hours/week and potential to grow.

Build and scale resilient ingestion, catalog, and derived data pipelines powering core infrastructure datasets. Own data contracts, schema governance, quality gates, automated testing, observability, and pipeline reliability. Modernize legacy systems into scalable platform architecture, including a graph database layer. Partner with global engineering, data science, ML, intelligence, and trust teams to support matching, confidence scoring, and automated workflows.

Leads a multidisciplinary marketing analytics organization spanning data engineering, analytics engineering, visualization, and data science. Builds attribution, ROI, customer journey, predictive signal, data governance, and AI-ready information architecture systems. Partners with Sales, RevOps, Finance, PLG, and Data teams to improve capital allocation and growth decisions. Oversees executive dashboards, metric alignment, team capacity, and strategic analytics delivery.

Build and operate production pipelines for legal records from PACER, court systems, opinions, PDFs, scans, XML, and HTML. Develop LLM-assisted extraction workflows, validate data quality, optimize SQL, and support RAG and semantic search products. Manage AWS S3 and RDS systems within security guardrails while collaborating with engineering teams. The role requires strong Python and SQL skills, legal data experience, document extraction expertise, and autonomous problem-solving with large, messy datasets.

Designs, develops, and maintains GCP-based security data pipelines and data products. Builds data quality and auditing frameworks, integrates security tools through APIs, optimizes BigQuery schemas and costs, and deploys automated ETL/ELT workflows using Python, SQL, and GCP services. Partners with security teams to deliver reporting views and dashboards. Cribl Stream experience is preferred for processing, enriching, routing, and reducing security telemetry and logs.

Designs and maintains end-to-end data solutions, including ETL/ELT pipelines, BigQuery platforms, APIs, semantic data layers, and data catalogs. Builds data quality monitoring, governance, security, and access controls while collaborating with analytics, product, engineering, and business teams. Requires strong Python, Kotlin, Java, SQL, API development, cloud data engineering, testing, and reliability experience.