Top Senior Data & Analytics Jobs in Dallas, TX

Manage GAINSCO’s enterprise data governance program, including governance councils, policies, business glossaries, data quality standards, stewardship, metadata, and master data management. Partner with IT, Security, Legal, Compliance, and business teams to improve data privacy, access, retention, audit readiness, and responsible AI practices. Facilitate cross-functional issue resolution, develop documentation and training, and support data literacy across the organization.

Leads the Data Engineering and Analytics team, managing people, technical strategy, intake prioritization, data pipelines, governed reporting, and stakeholder delivery. Oversees Python, SQL, dbt, Airflow, and BigQuery data products while guiding predictive analytics and machine-learning initiatives such as forecasting, recommendations, and segmentation. Establishes quality, reliability, governance, and development standards; mentors team members; supports debugging, process improvement, monthly reporting, invoices, and scorecards. The role also promotes responsible AI adoption and PHI-compliant data practices.

Owns end-to-end Collections and Recovery reporting and analytics, translating operational needs into SAS-based data processes, Tableau dashboards, validated datasets, and leadership-ready insights. Responsibilities include requirements gathering, data quality controls, trend analysis, automation, reporting governance, stakeholder partnership, and responsible use of AI. The role also mentors analysts and supports scalable, forward-looking performance measurement within a regulated financial services environment.

Designs, builds, tests, and supports enterprise data pipelines and Snowflake archival solutions for acquisitions, integrations, reporting, compliance, and analytics. Translates business and technical requirements into mappings, transformations, quality rules, and deployment plans. Collaborates with architecture, security, infrastructure, application, business, and vendor teams. Oversees validation, monitoring, documentation, cutover, go-live readiness, hypercare, and operational handoff while improving reusable, secure, cost-efficient data engineering practices.

Designs, builds, and operates enterprise data lakes, warehouses, lakehouses, ETL/ELT pipelines, databases, and reporting platforms. Prepares governed, model-ready data for AI and machine learning, supports feature stores and embedding workflows, administers relational databases, optimizes queries and dashboards, and ensures data quality, security, availability, and disaster recovery. Collaborates with technical and business teams, reports to senior management, and mentors data engineers.

Lead architecture and modernization of Azure-based enterprise data platforms for procurement analytics. Design and build Databricks/Delta Lake solutions, ETL/ELT pipelines, and harmonize ERP data into enterprise models. Define multi-year strategy, establish engineering standards, mentor engineers, evaluate tools, and deliver data products, APIs, and BI support. Influence technical direction and present roadmaps to stakeholders.

Aggregates enterprise data, develops advanced analytics and financial models, and delivers strategic insights to Growth leaders. Builds Snowflake semantic models, Cortex-based agentic analytics, Claude and Copilot Studio workflows, data mesh products, dashboards, and automated reporting. Uses Excel, Tableau, Streamlit, Salesforce, Alteryx, and AI orchestration to support forecasting, advisor profiling, growth initiatives, operational efficiency, and executive decision-making.

Leads loyalty analytics for 7Rewards and Speedy Rewards, managing analysts and translating customer, transaction, and campaign data into insights. Owns KPI frameworks, executive reporting, segmentation, incrementality measurement, campaign effectiveness, personalization, and ROI analysis. Partners across Marketing, CRM, Finance, Product, Operations, and Technology to influence strategy and improve member engagement, retention, frequency, and sales. Oversees data infrastructure, analytical standards, team development, and advanced analytics initiatives.

Lead architecture and modernization of scalable Azure-based data platforms for procurement analytics. Design and optimize ETL/ELT pipelines, Lakehouse architectures, and ERP integrations. Drive data engineering strategy, automation, CI/CD, governance, and AI-enabled productivity improvements while mentoring engineers and partnering with stakeholders to deliver reusable data products and APIs.

Designs and maintains secure, scalable data pipelines for structured and unstructured sources. Builds segmented data architectures with access controls, classification, governance, lineage, and auditability for sensitive environments. Optimizes workflows across cloud and hybrid platforms, supports production systems, and partners with technical, business, compliance, and cybersecurity stakeholders. The role enables analytics, AI/ML, and digital products while ensuring data integrity, performance, observability, and resiliency.