Top Analysis Reporting Jobs in Baltimore, MD

Develops and maintains secure data pipelines, ETL/ELT workflows, data transformations, and analytics-ready datasets. Processes structured and unstructured data using platforms such as Databricks, Spark, Palantir Foundry, and Maven Smart Systems. Collaborates with data scientists, engineers, and mission stakeholders while applying data validation, modeling, quality, testing, documentation, and Agile practices. The role requires onsite work in a SCIF and support for classified national security missions.

Analyzes pricing, compensation, sales performance, price realization, and competitive positioning. Manages pricing approvals, commissions, price lists, exchange rates, dashboards, and reporting. Partners with Sales, Marketing, and IT to identify process and system improvements, define business requirements, test implementations, document processes, and support CRM, CPQ, and other business-system initiatives. Develops metrics and programs that improve pricing effectiveness, operational efficiency, and profitable growth.

Design, build, and operate Azure-based data pipelines and integrations. Consolidate data from multiple sources into centralized SQL systems, perform transformations and field mapping, and maintain data warehouse capabilities. Troubleshoot quality, integrity, latency, security, and reliability issues while applying governance, monitoring, and SLA practices. Collaborate with engineers, analysts, and stakeholders in Agile pods to deliver reusable, analytics-ready data assets.

Administers Oracle, SQL Server, Sybase, PostgreSQL, and other databases, maintaining integrity, security, availability, performance, and recoverability. Responsibilities include user-account management, backups and disaster recovery, performance tuning, index maintenance, auditing, encryption, secure configuration, database server administration, and SQL/PL/SQL scripting. The role also evaluates DBMS products and develops policies and procedures supporting mission-critical systems.

Build and operate Sinclair’s enterprise Snowflake data platform, developing production pipelines, integrations, ELT models, data quality controls, observability, governance, and performance optimizations. The role requires hands-on Snowflake, Openflow, SQL, and Python expertise, production troubleshooting, enterprise integrations, deployment practices, and collaboration across technical and business teams. This is an on-site position in Hunt Valley, Maryland.

Leads and supports database design, development, administration, optimization, and maintenance. Develops database schemas, parser and loading software, queries, scripts, and macros while aligning structures with system architecture. Directs requirements fulfillment, data organization, storage and retrieval, and complex database systems using cloud methodologies. Requires extensive Oracle platform experience, Linux and Bash skills, a current poly clearance, and substantial database engineering experience.

Analyzes healthcare data using SAS, SQL, Excel, R, Python, Tableau, and related tools to identify trends, variances, outliers, and improvement opportunities. Creates reports, dashboards, tables, and visual presentations for technical and non-technical stakeholders. Supports healthcare intervention measurement, data entry, database functions, documentation, research, and policy compliance.

Conduct research, analyze complex business data, develop reports, document processes, present findings, and recommend improvements for customer projects. The role gathers stakeholder and survey information, evaluates business processes, anticipates requirements, and supports new solutions. It requires strong analytical, documentation, communication, organizational, presentation, and troubleshooting skills, along with Microsoft Office and SharePoint proficiency.

Design, build, and optimize scalable AWS and Snowflake data pipelines, databases, data models, and cloud-based solutions. Implement ETL/ELT workflows, data quality and monitoring frameworks, CI/CD pipelines, automated recovery, documentation, and performance improvements. Collaborate with stakeholders and cross-functional teams in an Agile environment while conducting advanced analysis using Python and SQL.

A one-year data engineering development program involving training, mentoring, and hands-on work designing, developing, testing, and delivering data assets and applications. Participants refine features, plan user stories, build data pipelines, apply SQL and data fundamentals, use AI and analytical tools, and collaborate with business and engineering teams. Occasional travel for business meetings and events is expected.