Top Senior Analysis Reporting Jobs in Dallas, TX

Builds and maintains enterprise data warehouse solutions, relational database schemas, ETL pipelines, and automated data processes. Responsibilities include optimizing complex SQL queries, indexing, execution plans, data modeling, governance, system support, and cross-functional delivery. Requires strong SQL, SSIS, data warehouse, and relational database expertise, with preferred experience in Azure Data Factory, ActiveBatch, and Snowflake.

Performs complex fraud analytics and financial modeling for money movement products. Uses SAS, SQL, Excel, Tableau, and databases to evaluate fraud risk, develop mitigation strategies, improve portfolio performance, and recommend policy changes. Leads reporting, strategy requirements, testing, and rollout activities, supports biometrics enhancements, and helps implement machine learning capabilities while communicating recommendations to senior management.

Designs and governs scalable Azure data platforms, lakehouse architectures, data models, ingestion pipelines, semantic layers, and governance frameworks. The role bridges insurance systems with analytical consumers, supports real-time and batch processing, enables Power BI and AI/ML solutions, and leads cloud migrations and architecture reviews. Responsibilities include mentoring data engineers, implementing data quality and lineage controls, securing data, and collaborating with technical and business stakeholders.

Leads enterprise data analytics, reporting, business intelligence, dashboards, data quality, and data governance supporting Texas child welfare services. Oversees data strategy, advanced analysis, system integration, documentation, and actionable insights for leaders, staff, funders, and policymakers. Supervises analytics personnel, manages priorities and budgets, promotes ethical data stewardship, and ensures compliance with child welfare regulations. Requires collaboration with operational leaders and translation of complex data into service improvement and outcome-focused decisions.

The Senior Data Analyst leads projects that improve operational performance and client service. Responsibilities include developing business strategies, monitoring operational risk metrics, collecting and presenting performance data, retrieving and optimizing data warehouse queries, mentoring team members in SQL, and communicating findings to operations staff and senior management. The role requires strong analytical, visualization, communication, and project management skills within a financial services environment.

Designs, builds, deploys, and operates scalable data pipelines and cloud-based data architectures supporting lending analytics across Mortgage and Personal Loans. Responsibilities include data ingestion and transformation, schema design, SQL optimization, workflow orchestration, monitoring, troubleshooting, data quality, and generative AI integration. The role also establishes engineering standards and collaborates with analysts, engineers, and governance teams to deliver reliable production data systems.

Build and maintain dbt data models, migrate Alteryx workflows, and manage Dagster or Airflow pipelines in Redshift. Partner with Revenue Operations stakeholders to translate data into business insights, dashboards, and KPI visibility using Tableau. Apply AI, LLMs, and machine learning through SageMaker to support predictive use cases such as churn prediction and lead scoring.

Leads customer-facing data solutions for IoT deployments. Monitors real-time data streams, analyzes data quality and system performance, investigates anomalies and root causes, and translates findings into actionable insights. Builds dashboards, partners with product and engineering teams to resolve issues, and guides customers on deployment best practices. The role also involves people or project management, big data architecture, analytics optimization, and integration work.

Owns the enterprise Data Lakehouse platform, including operations, configuration, integrations, monitoring, validation, issue resolution, vendor management, releases, documentation, security controls, and lifecycle planning. Translates business and data requirements into platform solutions, coordinates cross-functional technology teams, and ensures reliable support for business intelligence, reporting, analytics, and AI use cases. Provides technical leadership and guidance without direct personnel-management responsibility.

Uses advanced healthcare analytics to identify member and client needs, evaluate programs, develop predictive models and segmentation criteria, measure clinical, utilization, and financial outcomes, and guide product innovation and business strategy. Partners with clinical and business leaders, conducts applied research, develops analytical methodologies, addresses data limitations, and communicates findings through reports, white papers, conferences, and publications.