Top Data & Analytics Jobs

Data Analytics Interns will analyze large structured and unstructured datasets, develop insights and models, validate data, build dashboards and reporting tools, and automate repeatable analytics solutions. The role supports business decisions across insurance, care management, operations, and IT. Interns will present findings to leadership, collaborate cross-functionally, attend development classes, and participate in community service. Required qualifications include an analytical bachelor’s degree program, a 3.2 GPA, RDBMS experience, communication skills, leadership, and problem-solving ability.

Guidehouse is seeking a Data Scientist to collect and analyze data, develop visualizations, ensure data governance, and support decision-making for large-scale programs within DHS.

Analyze Customer Care performance, trends, KPIs, and data quality; gather reporting requirements; define metrics and business rules; validate data solutions; develop dashboards and visualizations; and translate findings into actionable recommendations. The role partners with business leaders and technical teams to modernize legacy reporting, improve scalability, ensure data accuracy, and enable self-service analytics.

Provides strategic and technical leadership for integrated data architecture, performance dashboards, data governance, analytics, verification tools, and data quality processes in Uganda. Translates program requirements into system and analytical specifications, integrates government data sources, identifies risks through data triangulation, and supervises information systems, monitoring and evaluation, and analytics managers. The role also supports government engagement, institutional ownership, proposal development, stakeholder relations, and team growth.

Designs and leads enterprise data architecture and strategy for an asset management business. Responsibilities include defining roadmaps, data platforms, architecture patterns, database models, data warehouses, data acquisition and distribution processes, governance, security, and AI solutions. The role requires hands-on prototyping with Snowflake, Azure, Databricks, SQL, and Python, while collaborating with global teams and influencing stakeholders across business and technology functions.

Build strategic data infrastructure roadmaps, design and implement complex ETL/ELT pipelines, and deliver scalable, secure data solutions. Collaborate across teams on cloud platform selection, data management, governance, privacy, and compliance. The role requires expertise in Databricks, Snowflake, data modeling, performance optimization, and pipeline automation.

Supports a global Army intelligence training program through process improvement, performance measurement, statistical and business analysis, risk identification, stakeholder surveys, process mapping, and knowledge management. Maintains records and databases for visualization and production activities, reviews analytic products for rigor and tradecraft standards, and develops research approaches and recommendations independently.

Design, implement, and maintain enterprise data pipelines, integration solutions, and data architecture. Use Qlik, DBT Labs, Snowflake, Astronomer, and Airflow for replication, transformation, storage, and analytics. Apply data engineering, modeling, ETL, warehousing, governance, security, and quality practices across cloud platforms. Troubleshoot data issues and collaborate with cross-functional stakeholders.

Leads the design, development, and operation of enterprise-scale data platforms and pipelines in Azure. Builds Lakehouse architectures using Databricks, Spark, Azure Data Factory, Synapse, and Data Lake Storage; implements data quality, monitoring, CI/CD, and governance practices; troubleshoots production issues; optimizes performance and scalability; collaborates with analysts, data scientists, and stakeholders; and mentors junior engineers.

Develops data-driven solutions, reports, dashboards, visualizations, and analytical models for a managed healthcare organization. The role validates data, improves processes, automates tasks, establishes data lineage, integrates diverse healthcare data sources, and presents actionable findings to business partners. It also explores AI and machine learning technologies, supports quality and operational improvements, and collaborates with informatics teams while working independently on multiple initiatives.