Top Data & Analytics Jobs in Baltimore, MD

Design, build, test, deploy, and support enterprise data solutions for financial reporting, reserving, and claims. Develop and maintain pipelines, transformations, data models, and controls using SQL, Python, PySpark, and Microsoft Fabric. Automate reconciliations and data quality checks, partner with business stakeholders, perform testing, review code, mentor peers, and resolve production issues to improve reporting accuracy and operational efficiency.

Lead Business Analyst partners with leadership to analyze data, evaluate processes, define requirements, build reports/dashboards, drive cross-functional improvements, and deliver executive-ready insights and recommendations to improve efficiency and business outcomes.

Lead design and implementation of end-to-end ELT pipelines and transformation layers (dbt) to produce curated, reporting-ready datasets. Define data models, governance, metadata, lineage, and engineering standards. Partner with cross-functional teams to translate requirements, optimize performance and costs (cloud DW like Snowflake), and grow a data architecture practice that supports BI, self-service analytics, and AI agents.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

The Fraud Reporting Analyst develops processes to analyze fraud-related data, identifies trends, and communicates insights to enhance fraud detection and operational performance.

Technical leader for Data Engineering responsible for designing, operating, and optimizing Snowflake-based data platforms, self-hosted orchestration (Prefect), dbt practices, AWS infrastructure, and data pipelines. Drive architecture, mentor engineers, partner cross-functionally, ensure observability and production-grade practices, and enable model-ready datasets and AI/LLM workflows.

Lead architecture and operations for the end-to-end data lifecycle: pipeline orchestration, dbt projects, cloud warehouse performance, dimensional modeling, data observability, HIPAA controls, and platform governance. Mentor a distributed data engineering team, partner with Analytics and Finance, and prioritize durable platform capabilities that enable BI, experimentation, and AI use cases.

Design, build, operate, and optimize large-scale production data pipelines and foundational Healthcare Map data products using Python, SQL, Airflow, Spark, and AWS. Ensure data quality, observability, and performance; debug complex workflows; contribute to architecture, CI/CD, testing, documentation, and cross-functional delivery to enable analytics and AI/ML use cases.

Validate and triage clinical data across HL7, FHIR, and Databricks pipelines using SQL. Trace transformations end-to-end, identify and remediate data quality issues, partner with engineering/product/clinical teams, document findings, and support client go-lives to ensure clinically accurate, production-ready data.

Lead and manage a remote Data Engineering team to build scalable data pipelines and lakehouse solutions. Own execution of Medallion architecture using Databricks, Boomi/Rivery, dbt, Delta Lake and SQL Server; implement DataOps, CI/CD, observability, and stakeholder intake while growing engineers and improving team maturity.