Top Senior Analysis Reporting Jobs in Baltimore, MD

Designs and maintains scalable Databricks data pipelines on AWS, covering ingestion, transformation, streaming, data quality, and analytics-ready dataset delivery. Builds medallion architecture layers using Spark, Python, SQL, Delta Lake, and AWS services. Responsibilities include source-to-target mapping, unit testing, CI/CD deployment, anomaly analysis, and compliance with FISMA High and multi-tenant governance requirements. Collaborates in Agile teams and uses AI automation tools to accelerate pipeline development and validation.

Designs and operates data infrastructure for a clinical trial platform. Builds pipelines that extract, normalize, validate, and link information from clinical documents and publications into Aurora and GraphDB. Develops embeddings, vector search, RAG workflows, data-serving APIs, lineage tracking, and regulatory audit trails. The role also requires AWS-based orchestration, clinical data quality controls, biomedical knowledge graph modeling, and deployment automation using infrastructure-as-code and containerization.

Own university data integrations from source discovery through validated, signed-off feeds. Build SQL queries and scheduled extracts, model data, support partner upgrades and migrations, translate institutional policies into accurate data feeds, and improve monitoring, documentation, and reusable integration patterns. Collaborate with registrars and database administrators while supporting a named set of university partners. The role requires deep experience with student information systems, including PeopleSoft, and occasional travel for partner onsite engagements.

Designs and maintains scalable data pipelines, warehouse models, and analytics solutions. Builds natural-language data interfaces using GenAI and LLM techniques, optimizes SQL, improves data quality and observability, and supports distributed data platforms on AWS or GCP. Partners with engineering, analytics, business, and product teams, contributes to shared codebases, establishes development standards, and participates in production on-call and incident response.

Leads data engineering, business intelligence, and analytics teams; oversees data pipelines, integration infrastructure, database architecture, CI/CD practices, and enterprise data platform strategy. Partners with business and technology stakeholders to define requirements, improve data capabilities, maintain Ubuntu-based services, and deliver reporting and KPIs to leadership. Responsible for team hiring, development, mentoring, operational health, and technical execution across analytics and data integration platforms.

Manage the health, performance, reliability, and cost of customer Snowflake and Databricks environments. Responsibilities include customer onboarding, account and warehouse setup, permissions, data ingestion, query optimization, cost reporting, incident response, escalation support, and automation using Python and Terraform. The role also advises customers and internal teams on data platform best practices and participates in on-call rotations.

Owns enterprise data governance activities, including metadata management, data cataloging, data quality rules, lineage, profiling, report certification, PII handling, and governance workflow automation. Partners with data stewards, IT teams, business stakeholders, and senior leaders to improve data integrity, regulatory compliance, reporting quality, and governance processes. The role also supports training, stakeholder workshops, process improvement, and mentoring of less experienced professionals.

Provides data management, database administration, performance reporting, QA/QC, and analytical support for NOAA environmental restoration programs. Develops Power BI dashboards, reports, data models, and visualizations; supports Power Apps, Dataverse, database processes, testing, and user acceptance. Translates program needs into technical requirements, documents business rules and procedures, trains users, troubleshoots data issues, and analyzes performance trends. Requires collaboration with program staff, project managers, leadership, and technical developers, with occasional travel and periodic on-site meetings.

Designs and implements the data architecture supporting engineering technology, analytics, automation, and AI. Assesses current systems, defines target architecture and governance, develops data models and ETL/ELT pipelines, integrates engineering platforms, and establishes metadata, lineage, stewardship, access, and quality standards. Partners with engineering and Digital Engineering teams to deliver reusable data assets, dashboards, and analytics solutions while coordinating data protection, platform evaluations, roadmaps, and stakeholder communication.

Build and maintain data lakes, data warehouses, and modern data pipelines for a multi-tenant SaaS platform. Design end-to-end data processes, write pipeline and infrastructure code, conduct design reviews, optimize performance, monitor systems, support data governance, and troubleshoot scalability and security issues. Collaborate with technical and business stakeholders, mentor junior engineers, evaluate technologies, document platform architecture, automate testing, and participate in on-call rotation.