Top Senior Data & Analytics Jobs in Baltimore, MD

Build and maintain scalable ETL/data pipelines and internal frameworks to support ML and product teams. Drive architecture, observability, data quality, and engineering best practices across AI/ML workflows and prompt-engineering pipelines.

Build governed gold-layer data models and a single-source metrics layer in Snowflake (dbt); create and optimize dashboards in enterprise BI tools; use AI coding agents and AI-assisted tooling to accelerate development; ensure data quality, governance, and consistency; collaborate with data engineering and stakeholders to deliver trusted analytics for internal and client-facing use.

Client-facing BI consultant responsible for end-to-end delivery of TARGIT-based analytics: requirements gathering, prototyping, backend work, dashboards, training, deployment, optimization, and customer engagement.

Lead enterprise data strategy and governance, build AI-ready data infrastructure and BI systems, own SharePoint platform, partner cross-functionally to ensure data quality, access, compliance, and user adoption.

Design and maintain enterprise data architecture across AWS and Azure, lead Snowflake data warehouse strategy, ensure data governance and HIPAA compliance, enable BI and AI/ML pipelines, collaborate with engineers and stakeholders, and recommend modern data technologies and standards.

Design and implement scalable Azure-based data architectures and analytics solutions, lead delivery teams, support pre-sales, drive DevOps/CI-CD, mentor junior staff, define data strategy, governance, migrations, and oversee project delivery and backlog management.

Bridge enterprise customers' legacy BI to Hightouch by reverse-engineering complex marketing reports, building reusable reporting frameworks, engineering and documenting semantic/context layers, ensuring accurate SQL generation, and training non-technical marketers while collaborating cross-functionally to deliver reliable, idempotent AI-driven analytics.

Lead full-stack analytics at Air by designing and maintaining dbt models and BigQuery transformation layer, ensuring data quality and observability, owning ingestion/orchestration, building self-serve BI (Mode/Hex) and AI-native interfaces, and partnering with product, growth, and GTM teams to deliver trusted data products and strategic insights.

Design, build, and maintain scalable data pipelines, data models, ETL/ELT, and BI solutions. Collaborate with data scientists and stakeholders to improve data quality, accessibility, and PHI security. Develop and document workflows, optimize processing/storage, support data warehouse and visualization, and adopt AI tools to drive data-informed outcomes.

Build and maintain scalable monitoring solutions and dashboards to track production, campaign, and operational data. Analyze large-scale datasets to detect anomalies, perform root-cause investigations with Engineering and Production Operations, and deliver actionable insights to improve platform reliability and operational efficiency.