Top Data & Analytics Jobs in Greensboro, NC

Build customer-facing data products for the single-family rental market. Responsibilities include architecting real estate data models, designing reliable data pipelines and workflows, shaping data platform architecture, establishing engineering standards, and developing real estate domain expertise. The role partners with data science and product teams and requires leadership in scalable data engineering.

Designs and implements scalable data pipelines, cloud data platforms, storage solutions, and analytics infrastructure. The role focuses on Snowflake and AWS architecture, migrating legacy systems to cloud environments, developing Python and SQL data-processing logic, orchestrating workflows, and implementing Infrastructure-as-Code and CI/CD. The engineer also contributes to data governance, quality, observability, stakeholder communication, mentoring, and technical leadership.

The Senior Data Analyst will develop and improve Sigma dashboards, reporting, and business intelligence capabilities. Responsibilities include gathering stakeholder requirements, querying and analyzing complex datasets with SQL, improving data quality and governance, defining metrics, automating reporting processes, and partnering on Snowflake data modeling and warehouse improvements. The role also evaluates analytics tools, delivers actionable insights, and communicates findings to technical and non-technical audiences.

Monitors, validates, and improves data quality across device, program, operational, and field sources. Designs automated checks, reconciles discrepancies, investigates root causes, documents findings, and communicates impacts and recommendations. Collaborates with analytics, engineering, MEAL, and country teams to resolve issues. Maintains reproducible analyses using SQL, programming, version control, and notebooks while supporting data governance, reporting standards, and responsible handling of sensitive information.

Build and operate Imagine Worldwide’s AWS- and ClickHouse-based analytics platform, including infrastructure, data lakes, Spark processing, ingestion pipelines, Airflow orchestration, dbt models, CI/CD, monitoring, security, backups, and cost optimization. Process billions of device events and integrate program context into reliable analytical datasets. The role also involves incident response, documentation, architectural contributions, and collaboration with globally distributed analytics and operations teams.

Lead Workday reporting strategy for higher education: design Advanced, Matrix, Composite, and Dashboard reports; implement row-level security and role-based access; partner with HR/Finance/Payroll/Institutional Research; support regulatory and executive reporting; manage testing, validation, and user training while ensuring governance and data standards.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Build and operate data pipelines ingesting and normalizing security data from multiple sources. Own entity resolution, asset attribution, data quality monitoring, automated correlation logic, and reporting support. Collaborate with security analysts and leadership to turn noisy data into actionable insights and improve remediation outcomes. Contribute to AI-augmented data analysis and correlation capabilities.

Designs scalable data architectures, pipelines, schemas, and cloud-based storage solutions for high-volume structured and unstructured data. Ensures data quality, security, compliance, performance, and cost efficiency while applying AI and machine learning techniques. Builds enterprise AI agent orchestration systems using LangGraph and LangChain, partners with data scientists and stakeholders, develops reporting tools, and leads end-to-end technical projects.

Lead enterprise data engineering efforts supporting defense missions. Responsibilities include prioritizing technical tasks, mentoring engineers, conducting code reviews, translating government requirements into scalable data architectures, developing Databricks ETL/ELT pipelines with Python, PySpark, and SQL, troubleshooting pipeline performance and reliability, and documenting systems. The role collaborates with government stakeholders, product owners, data scientists, analysts, and technical teams to deliver secure, high-throughput data platforms and actionable insights.

Designs and optimizes enterprise data models and Power BI semantic layers for reporting, forecasting, self-service analytics, and AI use cases. Develops dimensional models, DAX, SQL, and Power Query solutions; integrates enterprise data sources; validates data quality; optimizes performance; implements security and governance; and supports production datasets. Partners with technical and business stakeholders on requirements, documentation, metric definitions, deployment practices, and analytical solutions.

Designs and automates data validation, profiling, testing, monitoring, and quality frameworks for multi-source cloud data. The role uses Azure Synapse, Databricks, SQL, Python, Scala, Collibra, and Profisee to detect anomalies, enforce governance, and improve data reliability. Responsibilities include developing automated test plans, analyzing structured and unstructured datasets, supporting Azure data engineering workflows, and collaborating with engineers, analysts, data scientists, and product teams. A Public Trust or Suitability/Fitness determination may be required.

Designs and maintains scalable Azure data pipelines and ETL/ELT solutions across data lakes, warehouses, lakehouses, streaming platforms, and enterprise sources. Builds integrations using Azure Data Factory, Synapse, Databricks, Spark, Kafka, and related services; applies security, governance, monitoring, and performance optimization practices. Develops Power BI dashboards, reports, data models, and visualizations, while supporting analytics and AI/ML use cases. Collaborates in Agile teams and automates deployments through DevOps and CI/CD practices.

Designs, maintains, and optimizes SQL Server databases, ETL/ELT workflows, and enterprise data pipelines supporting a federal multi-cloud analytics platform. Integrates structured and unstructured data using Azure, Databricks, Starburst, and data lakes; troubleshoots failures, tunes performance, applies data-quality and governance controls, and supports analytics, reporting, and machine-learning use cases. Translates business requirements into technical solutions and documents data products, pipelines, and operational procedures.