Top Senior Analysis Reporting Jobs in Baltimore, MD

Partner with People teams to turn HR and org data into actionable insights. Build complex queries, statistical analyses, dashboards, and a centralized people data repository. Drive data governance, data quality, and stakeholder communication to support hiring, retention, productivity, and workforce decision-making.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Plans and implements data management processes for defense programs. Reviews contracts to determine documentation requirements, schedules and tracks contractual data deliverables, coordinates customer requirements, performs quality reviews, reports data status, manages electronic and physical deliveries, archives work products, and flows requirements to subcontractors through SDRLs. The role requires active Secret clearance, SAP eligibility, U.S. citizenship, strong communication and leadership skills, and experience with CDRL processes.

Develops, administers, and supports enterprise data platforms, pipelines, ETL processes, and automation tools. Responsibilities include SQL development, data integration, semantic modeling, performance tuning, troubleshooting, security and governance, user access management, monitoring, testing, documentation, and technical support. The role collaborates with architects, developers, governance teams, and stakeholders; mentors developers; supports roadmap planning; and provides on-call assistance for data platforms and processes.

Lead the architecture and zero-to-one implementation of a governed Databricks enterprise data platform. Define medallion architecture, data models, MDM and golden-record patterns, governance-as-code, integrations, APIs, data quality standards, and secure data-product delivery. Partner with engineering, governance, mission, and client teams, guide implementation, communicate technical direction, and ensure compliance with security and regulatory requirements.

Develops and supports Oracle database solutions, including complex SQL and PL/SQL objects, performance tuning, security, data governance, quality management, and migration initiatives. Performs ETL/ELT, data validation, reconciliation, conversion, and post-migration verification while maintaining metadata, lineage, documentation, and data dictionaries. Collaborates with data owners, developers, DBAs, business users, and project managers. Requires five or more years of Oracle development experience and an active TS/SCI clearance with polygraph.

Develop and maintain high-performance cloud-based analytics solutions processing large data volumes. The role requires expertise in data analytics, big data, distributed computing, and technologies such as Spark, MapReduce, SQL/NoSQL, and scientific Python libraries. The engineer will support mission-critical software and systems for a U.S. Government customer, working independently and collaboratively while contributing to a technical, security-focused engineering environment.

Leads database architecture, administration, migration, performance tuning, security, resilience, and production support for a CRM modernization effort. Migrates Oracle Siebel data to AWS PostgreSQL environments, develops ETL processes, validates data quality, supports integration with Pega and enterprise systems, and ensures compliance with availability, FedRAMP, and CMS requirements. Provides technical guidance, documentation, troubleshooting, cutover support, and stakeholder communication.

Build and maintain production data ingestion, transformation, and pipeline systems for a governed federal data and AI platform. Develop data products, contribute to Terraform infrastructure and CI/CD, monitor quality and reliability, troubleshoot issues, and apply governance and access controls. Support data science and ML teams while operating within FedRAMP, NIST 800-171, and CUI requirements. Collaborate with engineers and document pipelines and processes.

Serve as the healthcare program-integrity and fraud, waste, and abuse authority for an AI proof of concept supporting CMS. Select fraud use cases, curate ground-truth datasets, validate AI-generated leads and case files, translate investigator workflows into acceptance criteria, and ensure outputs reflect Medicare and Medicaid fraud investigation practices. Partner with engineers, investigators, CMS stakeholders, and law-enforcement organizations on evaluation, adoption, onboarding, and training.

Develop and maintain enterprise data engineering and business intelligence solutions. Build and optimize SQL queries, datasets, dashboards, reports, ETL/ELT processes, and data integrations using Python and BI platforms. Analyze and validate complex data, resolve quality and performance issues, support data modeling, and translate stakeholder requirements into technical solutions. Collaborate across technical and business teams using Agile practices, Jira, and GitHub while documenting and improving scalable reporting systems.