Top Remote Analysis Reporting Jobs in Greensboro, NC

No job description, responsibilities, or qualifications were provided. Title suggests a combined Data Engineer and Business Analyst role, likely involving data pipelines, ETL, data modeling, and business requirements/analytics, but specifics are not available.

Lead enterprise data strategy and governance, build AI-ready data infrastructure and BI systems, own SharePoint platform, partner cross-functionally to ensure data quality, access, compliance, and user adoption.

Lead design, build, and operate scalable Databricks/Delta Lake data pipelines and Kimball dimensional models using dbt. Manage governance with Unity Catalog, optimize performance and cost, operationalize ML with MLflow, and coordinate/quality-check offshore vendor engineering. Mentor engineers, uphold standards, and deliver trusted data products that power analytics, reporting, and MLOps workflows.

Design and maintain enterprise data architecture across AWS and Azure, lead Snowflake data warehouse strategy, ensure data governance and HIPAA compliance, enable BI and AI/ML pipelines, collaborate with engineers and stakeholders, and recommend modern data technologies and standards.

Design and implement scalable Azure-based data architectures and analytics solutions, lead delivery teams, support pre-sales, drive DevOps/CI-CD, mentor junior staff, define data strategy, governance, migrations, and oversee project delivery and backlog management.

Supervises Data Services team focusing on data engineering and operations, ensuring alignment with IT policies, data governance, and operational reliability of data products.

Partner with Ads sales to provide data-driven prospecting, reporting, and strategic recommendations. Build SQL queries and dashboards, produce monthly/quarterly client narratives, run incrementality/A-B tests, and present insights to brands. Support new business pitches, automate reporting workflows, and collaborate with Sales, Ad Ops, and Product on ad performance and product testing.

Design, build, and maintain cloud-based ELT data pipelines and analytics-ready datasets using Snowflake, dbt, and integration tools (Fivetran/Airbyte). Implement CDC and incremental loading, optimize Snowflake performance, enforce data quality and monitoring, create dimensional models for reporting, enable CI/CD for dbt projects, and collaborate with analytics and stakeholder teams to support reporting and advanced analytics.

Analyze large datasets to identify trends and deliver actionable insights; design and monitor KPIs; build and maintain dashboards and reporting frameworks; conduct ad hoc analyses; ensure data quality and support reporting infrastructure in partnership with product and business teams.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.