Top Senior Analysis Reporting Jobs in Washington, DC

Supports client data and analytics engagements by designing validation approaches, building data integration and transformation solutions, analyzing data quality issues, testing pipelines with SQL, documenting findings, and recommending corrective actions. The role collaborates with clients, manages workstreams, mentors junior team members, and applies Agile methods while delivering risk and regulatory data solutions.

Own analytics engineering for the machine infrastructure supply chain team. Build and maintain semantic layers, trusted data models, metrics, dashboards, and analytics-ready datasets using dbt and modern data platforms. Analyze inventory trends, optimize stock levels, investigate discrepancies, and develop supply chain KPIs. Partner with data engineering, finance, product, operations, planners, and buyers while improving inventory planning, replenishment, ERP processes, and warehouse efficiency.

Lead data analysis projects to help merchant partners understand Upside's impact, manage analytics relationships, and improve product strategy.

Develop and maintain Power BI dashboards, reports, data models, and visualizations supporting commercial sales decisions. Translate business requirements into scalable analytics solutions, improve forecasting and performance reporting, troubleshoot data and reporting issues, validate releases, and maintain DataMart reliability. Partner with sales leaders, business analysts, stakeholders, and technical teams while following governance and development standards.

Leads and transforms a sales performance analytics organization into a strategic, insight-driven business partner. Oversees analytics products, dashboards, forecasts, KPIs, governance, adoption, data quality, and responsible AI initiatives. Partners with senior sales, business, and technical leaders to rationalize reporting portfolios, prioritize high-value analytics, guide technical delivery, and translate complex data into actionable decisions. Coaches a multidisciplinary team and leads organizational change across a complex commercial environment.

Leads end-to-end analytics projects for FINRA’s regulatory operations, including scoping quantitative methods, developing predictive pipelines, expanding data sources, and delivering analytics capabilities. Promotes advanced analytics adoption, supports cross-market surveillance, engages stakeholders, responds to research requests, and mentors analysts. Requires collaboration across delivery teams and participation in strategic analytics initiatives.

Analyze large and complex datasets to identify trends, clean and transform data, query databases with SQL, and develop dashboards and visualizations using Databricks, Tableau, Power BI, and Excel. Produce analytical reports and recommendations, apply predictive analytics when appropriate, and support agile delivery through user story documentation and testing.

Owns the enterprise Data Lakehouse platform, including operations, configuration, integrations, monitoring, data validation, issue resolution, vendor management, releases, documentation, security controls, and lifecycle improvements. Translates stakeholder requirements into data solutions, coordinates cross-functional technology teams, guides platform initiatives, and ensures reliable support for business intelligence, reporting, analytics, and AI use cases.

Designs and maintains the firm’s Azure and Databricks Data Lakehouse architecture. Translates business, reporting, analytics, and AI requirements into scalable data structures, integrations, pipelines, and secure data solutions. Evaluates data sources, develops mappings and connectors, applies modeling and data quality practices, documents architecture, resolves integration issues, and guides downstream developers. Collaborates with stakeholders, application owners, database teams, and technology resources while evaluating emerging cloud, analytics, automation, and AI technologies.

Leads business intelligence strategy, dashboard development, data analysis, automation, and a small BI analyst team. Builds Power BI solutions using data from financial, sales, customer success, CRM, and operational systems. Partners with data engineering and business leaders to ensure data quality, deliver actionable insights, support customer retention and expansion, and present recommendations to executives. Provides technical direction, mentorship, prioritization, documentation, and end-user training.

Build and maintain dbt data models while migrating workflows from Alteryx, orchestrating pipelines with Dagster or Airflow, and managing Redshift data infrastructure. Partner with RevOps stakeholders to translate data into actionable business insights and Tableau dashboards. Explore AI, LLM, and machine learning applications using SageMaker for predictive analytics, churn prediction, lead scoring, ABM, and customer health scoring.

Builds and operates scalable Azure data pipelines, storage, datasets, and data products for analytics and operational insights. Responsibilities include Azure Data Factory development, Blob Storage and Azure SQL optimization, dimensional and Data Vault modeling, data quality and governance, security, monitoring, troubleshooting, CI/CD, and performance optimization. Collaborates with analytics, product, and operations teams to deliver reliable, documented data solutions. Desired experience includes Synapse, Fabric, Power BI, streaming technologies, infrastructure as code, and data cataloging.