Top Data & Analytics Jobs

Manages DoD data, records, configuration, and change-management processes. Maintains CDRLs, equipment inventories, records plans, databases, and SharePoint environments; supports audits, data requirements, reporting, compliance, and database administration. Collaborates with government staff and contractors, provides user support, develops management briefings, and ensures cybersecurity and information-security practices are followed.

Develops and implements data engineering and statistical analysis solutions for government customers. Responsibilities include automating data extraction and processing, building data models, analyzing large and diverse datasets, developing statistical methods, creating databases, reports, and visualizations, and communicating technical findings. The role requires independent problem-solving, data science and engineering experience, and support for intelligence-related data capabilities.

Own Fullbay’s Snowflake data platform end to end, including dimensional modeling, certified metric definitions, semantic layers, identity resolution, transformations, governance, security, cost management, source ingestion, and AI-agent enablement. Build tested SQL and transformation code, establish company-wide data standards, document systems thoroughly, and direct an architecture consultant. Provide guidance for self-service data use while serving as the final authority on definitions, access, and platform design.

Maintain and troubleshoot Airtable systems and API integrations connecting Salesforce, Coupa, AWS finance tools, and operational data sources. Support automated reporting, dashboards, executive performance reports, data validation, documentation, naming standards, and metadata governance. The role focuses on testing, reliability, issue resolution, and onsite support, with mentorship from a Senior Data Operations Architect.

Leads enterprise information systems, Power BI reporting architecture, data governance, analytics, ERP initiatives, and AI tool adoption. Builds and validates dashboards, ensures data quality, manages system operations, and supports business decision-making. Partners with IT and business stakeholders, provides proactive communication, leads and develops IS staff, manages vendors and budgets, and drives enterprise application delivery and improvement.

Develop and manage Workday PSA and Financials data solutions, including conversions, transformations, integrations, reporting, APIs, EIBs, and ETL processes. Create technical documentation, perform data analysis and loading, support migrations and M&A initiatives, and ensure security, compliance, access controls, and data quality. Partner with business analysts, functional leads, engineers, and security teams while managing multiple projects and serving as a Workday data subject matter expert.

Build and maintain a production data platform integrating RMS, Azure SQL, HubSpot, and vendor APIs. Develop pipelines, data models, quality gates, APIs, system-of-record write-backs, performance improvements, and explainable lineage. Build production AI-agent workflows with evaluation, guardrails, and monitoring. Own features end to end, contribute to applications, support incident response, and collaborate with product managers and traders.

Technical lead for Finance Technology data engineering: design and build scalable batch and real-time data pipelines (Hadoop/Spark/PySpark/Scala/Java), optimize data models and APIs, drive cloud-based data architecture (AWS/GCP/Azure), enforce governance/security, and mentor engineers to deliver enterprise financial data services.

Provide senior-level data engineering for analytics: resolve complex technical issues, build decision-support reports and dashboards, lead projects, prepare and integrate data, coach staff, and ensure high-quality analytics to support academic, research, and healthcare goals.

Develops and maintains dbt models in Snowflake, transforms source data into governed analytical datasets, and designs dimensional data models. Builds Gold-layer data products supporting Power BI, reporting, analytics, and approved AI use cases. Implements data quality tests, documentation, lineage, source control, CI/CD, and production monitoring. Partners with business stakeholders, analysts, and Data Engineering to define metrics, troubleshoot data issues, validate releases, and support certified semantic datasets.