Top Data & Analytics Jobs in Washington, DC

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.

Provides analytics and strategic advisory support for mergers, acquisitions, and other business transactions. Analyzes contract data to identify risks, obligations, performance insights, and compliance indicators; develops algorithms, data models, pipelines, dashboards, and predictive models using Python and machine learning. Collaborates with clients and internal teams, validates data integrity and security, mentors junior staff, and delivers data-driven recommendations.

Own and maintain dbt data models across design, testing, deployment, monitoring, and documentation. Translate ambiguous Marketing and Product needs into reliable data solutions, write design documents, support production issues, create runbooks and schema documentation, and coach junior engineers. The role uses SQL, Python, Snowflake, dbt, Dagster, and AWS while partnering closely with Marketing, Data, and MarTech teams.

The Deployment Strategist collaborates with teams to deploy software solutions, analyze data, and train customers while addressing complex operational challenges.

Develop and maintain enterprise Power BI solutions, including dashboards, reports, semantic models, data transformations, SQL queries, security controls, refreshes, and deployment pipelines. Translate business requirements into scalable analytics solutions, optimize performance, troubleshoot data and connectivity issues, document solutions, support testing, and collaborate with technical and business stakeholders. Provide guidance to junior staff and present analytical findings to technical and non-technical audiences.

Lead growth analytics for Zendesk’s product-led growth motion, guiding a team of analysts and partnering with Product, Engineering, Sales, Marketing, and Data teams. Define funnel metrics, measurement plans, experiments, and instrumentation across acquisition, activation, conversion, retention, and expansion. Analyze customer behavior using segmentation, cohorts, funnels, experimentation, and statistical methods. Improve self-service reporting, dashboards, metric definitions, reusable datasets, and analytics capabilities while coaching analysts and influencing senior stakeholders.

Analyze, clean, transform, validate, and document structured and unstructured datasets for federal analytics and AI-enabled systems. Maintain data pipelines, develop Power BI or similar dashboards, conduct exploratory analysis, identify data-quality issues, automate reporting workflows, and communicate findings to technical and non-technical stakeholders. Ensure data products meet federal standards for accuracy, governance, compliance, and usability.

Analyzes complex structured and unstructured data for National Security clients, developing methodologies, models, visualizations, metrics, and recommendations. The role involves data wrangling, statistical analysis, Python-based interfaces, Tableau or Matplotlib visualizations, and presenting findings to clients and stakeholders. The analyst supports cross-functional decision-making, handles protected data and ethical AI practices, and requires knowledge of military and Intelligence Community environments.

Analyzes large structured and unstructured datasets for Customs and Border Protection clients, developing data methodologies, metrics, KPIs, visualizations, and recommendations. Translates technical findings into actionable insights, supports business process improvement, and advises stakeholders on data-driven decisions. Uses SQL, Python, R, Microsoft Power Platform, AI tools, databases, and presentation software to deliver client-facing data solutions.

Own data quality and operational reliability across Snowflake data pipelines. Responsibilities include monitoring jobs, managing incidents, maintaining runbooks, administering Monte Carlo, creating data quality checks and dashboards, validating bordereau and financial data, supporting UAT and integrations, analyzing trends, and partnering with engineering and business stakeholders to resolve data issues and improve processes.

Leads complex analytics initiatives and partners with business leaders to define problems, analyze pharmacy, sales, and operational data, and develop actionable recommendations. Manages engagements across the full analytics lifecycle, from discovery through solution delivery and implementation support. Designs metrics, dashboards, frameworks, and decision-support tools while communicating insights to executive, operational, and technical audiences. The role emphasizes consultative analytics and business problem solving rather than software development or data infrastructure engineering.