Top Remote Analysis Reporting Jobs in Dallas, TX

Lead a BI team to design, develop, and maintain enterprise dashboards, KPIs, and reports. Collaborate with stakeholders, ensure data governance and quality, integrate BI with cloud data warehouses and ETL pipelines, and support ERP migration to cloud. Drive BI strategy, documentation, training, and continuous improvement to enable data-driven decisions across the company.

Lead enterprise data architecture and governance across Microsoft Fabric, Azure, EDW and analytics. Define integration patterns, data modeling, lineage, security, DR/continuity and vendor standards. Guide engineering teams on implementation, performance tuning, cost optimization, testing, and responsible AI/GenAI integration. Ensure solutions meet regulatory, audit, and operational requirements while collaborating with business and IT stakeholders to translate needs into long-term platform roadmaps.

Design and deliver enterprise data infrastructure and architectures across on-prem and Azure cloud. Build ETL/ELT pipelines, data models, governance, security, and migrations; mentor teams and align data platforms to business, compliance, and analytics needs.

Create and validate complex datasets for AI benchmark tasks, including files with malformed records, missing data, truncations, and inconsistent formatting. Define correct final states, write detailed grading rubrics, and assess AI outputs for accuracy and completeness. The role requires exceptional attention to detail, error detection, format reconciliation, accurate documentation, and clear asynchronous communication in regulated or audit-sensitive contexts.

Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

Design and own an event-driven data architecture that moves healthcare claims data through AWS and Snowflake into fraud, waste, and abuse alerts. Establish architecture standards, approve material changes, build complex pipeline components, and ensure scalability, reliability, and compliance with PII/PHI constraints. Collaborate with data science, compliance, technical, and investigative teams while supporting government review timelines. This is a hands-on principal role requiring strong Python, SQL, AWS, Snowflake, and production streaming pipeline experience.

Design, develop, and optimize scalable Databricks data pipelines using PySpark, SQL, Spark, and Delta Lake. Build workflows, ingestion and transformation processes, data quality checks, monitoring, and CI/CD automation. Optimize distributed workloads, configure Databricks compute, support cloud governance and access controls, troubleshoot production issues, and collaborate with technical and research stakeholders to deliver secure, reliable analytical datasets.

Lead a remote analytics team to deliver dashboards, data products, and decision-support tools. Oversee project plans, stakeholder engagement, data platform modernization, ETL/automation, Tableau/Power BI deployments, statistical modeling, QA, metadata, and staff mentoring to support federal social service programs.

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.

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.

Build and maintain IICS ETL/ELT pipelines, develop Amazon Redshift data models, and use SQL and Python for data transformation and automation. Create Power BI reporting models, implement data quality checks, document pipelines, and collaborate with client stakeholders and engineering teams. The role requires autonomous work, strong communication, and the ability to translate technical solutions into business context, with bonus value for Veeva or life sciences experience.

Leads legacy data migration into SaaS platforms by assessing sources, designing conversion strategies, executing ETL workflows, mapping and transforming data, validating integrity, and managing PII. Engages clients to gather requirements, document business processes, support governance and data quality, coordinate implementation teams, and develop reusable methodologies and training materials.

Own data quality across systems by designing validation rules, reconciliation processes, profiling workflows, and quality controls. Investigate discrepancies to identify root causes, apply statistical methods to detect anomalies, evaluate machine learning model outputs, and communicate findings to technical and non-technical stakeholders. Partner with engineering, BI, and business teams to establish data quality standards, metrics, controls, and reporting practices.