Top Senior Analysis Reporting Jobs in Greensboro, NC

Designs and maintains scalable data architecture, warehouses, ETL/ELT pipelines, and data platforms. Responsibilities include ensuring data quality, integrity, governance, accessibility, reliability, and performance; supporting customer onboarding and analytics tools; contributing to architecture and engineering best practices; troubleshooting complex data issues; and participating in on-call rotations. The role collaborates with engineering, product, solutions, business intelligence, and other cross-functional teams in healthcare and social care data environments.

Designs, implements, and maintains data pipelines, integration solutions, and data architecture using Snowflake and related data engineering tools. Analyzes insurance industry challenges, develops solutions, supports consulting engagements, presents recommendations, and collaborates with client stakeholders. The role also requires data modeling, ETL, cloud platforms, data governance, troubleshooting, and the ability to manage multiple initiatives while traveling up to 50%.

Analyze clinical data completeness, reliability, and effectiveness across healthcare facilities, vendors, interoperability networks, and integration pathways. Reconcile claims with clinical records, identify missingness and latency, report ADT coverage, evaluate data technologies, recommend vendor configurations, and prioritize facilities for direct acquisition. Partner with product, engineering, and clinical teams to improve scalable, trustworthy data pipelines and support TEFCA and QHIN strategy.

Leads customer data engineering strategy, delivery, team development, and roadmapping. Oversees data-driven product improvements, digital programs, quality initiatives, budgets, cybersecurity remediation, and portfolio management. Manages, mentors, and grows data engineering teams, including contractor teams, while guiding customer data platforms, omnichannel identity resolution, complex data modeling, and personalization-focused data science capabilities. Partners across the organization to execute strategic initiatives and build team capability.

Lead complex customer analytics engagements, translating industrial business needs into scalable analytics architectures and solutions. Advise customers, drive product adoption, identify high-value use cases, mentor Analytics Engineers, resolve technical escalations, and influence product roadmaps. Apply expertise in industrial process data and sectors such as power, pharmaceuticals, and semiconductors. Collaborate with customers, partners, product teams, and account teams to deliver measurable business outcomes.

Designs, analyzes, documents, integrates, and migrates complex environmental datasets for AirHub business lines. Responsibilities include analyzing legacy databases, creating logical and physical data models, documenting mappings and business rules, developing migration specifications and API integrations, supporting data governance and testing, and producing technical documentation. The role also requires close collaboration with business stakeholders in an Agile delivery environment.

Develops scalable data models, Databricks pipelines, backend applications, ETL processes, and data ingestion systems. Partners with engineering, product, and business stakeholders on technical roadmaps; monitors and optimizes data systems for performance, reliability, and scalability. Provides technical leadership, mentors junior engineers, conducts code reviews, and builds secure solutions for sensitive healthcare data.

Lead BI reporting and advanced analytics to optimize marketing campaigns and ROI. Build dashboards, manage multi-source data, ensure data governance, provide actionable insights, mentor juniors, and partner with cross-functional teams to guide strategy.

Build and operate scalable cloud data pipelines, warehouses, transformation layers, and ML production systems. Lead data infrastructure architecture, warehouse performance optimization, DataOps monitoring, CI/CD improvements, data quality testing, and large-scale data product delivery. Collaborate across teams, promote data stewardship, and support batch and streaming pipelines while deploying, serving, and monitoring machine learning models.

Own the architecture and technical direction of Northbeam’s data ingestion and integration platform. Design scalable API-based ETL, event-driven and batch processing systems; establish standards for observability, freshness, and failure handling; and guide build-versus-buy decisions. Collaborate across engineering, infrastructure, product, and business teams while mentoring engineers, leading design reviews, and driving complex platform initiatives to completion.