Top Senior Analysis Reporting Jobs in Dallas, TX

Leads BI, analytics, and AI initiatives that transform energy market and customer data into dashboards, automated insights, predictive analyses, and strategic recommendations. The role supports pricing, acquisition, retention, marketing, finance, and customer experience decisions through Python, SQL, Tableau, Power BI, generative BI, experimentation, and machine learning. Responsibilities include building executive reporting, evaluating AI-enhanced BI platforms, analyzing customer lifecycle performance, mentoring analysts, and partnering with cross-functional business and technical teams.

Develops AI, analytics, SQL, Python, and Tableau solutions for Internal Audit across risk assessment, planning, testing, reporting, and continuous monitoring. Builds data extraction and reconciliation workflows, audit dashboards, repeatable testing scripts, and AI-assisted tooling. Assesses data lineage, controls, and risks across business systems, supports GRC administration, identifies automation opportunities, and trains audit staff on analytics and AI-enabled workflows.

Analyze large datasets to identify opportunities that improve customer experience and profitability. Build and automate reporting, develop quantitative analyses and visualizations, and provide strategic recommendations to senior leaders. The role uses Excel, SQL, Snowflake, R, and Tableau while collaborating across teams, managing multiple project streams, and designing and implementing new products and solutions.

Designs, builds, and maintains scalable Azure data pipelines and ELT frameworks using Databricks, SQL, Python, and PySpark. Implements Azure DevOps CI/CD, monitoring, security, infrastructure automation, and production support. Collaborates with BI teams on Power BI datasets, documents data solutions, participates in Agile delivery, and mentors junior engineers. The role requires strong data modeling, structured and semi-structured data expertise, performance tuning, and data governance awareness.

Leads consulting engagements involving scalable data architecture, real-time and batch pipelines, ETL/ELT, data modeling, cloud data platforms, governance, and production support. Designs data lakes and warehouses, develops efficient SQL and Python solutions, establishes data quality and performance KPIs, and collaborates with technical and business stakeholders. The role also includes code reviews, metadata management, and advising clients on data lifecycle and analytics capabilities.

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.

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.

Conduct market, competitor, financial, and industry research for the Technology, Media, and Telecommunications practice. Identify prospects, support business development proposals, provide account intelligence, and translate quantitative and qualitative analysis into actionable insights. The role also supports AI-powered research tools and workflows, collaborates with senior leaders, and delivers executive-ready communications in a fast-paced consulting environment.

The Director of Customer Data Engineering will manage customer data strategies, ensuring compliance and privacy while leading data integration and governance initiatives. They will drive data quality and enhance business intelligence investments, collaborating across global teams and building a strong technical team.

Design, build, and operate scalable batch and streaming data pipelines and analytical data models. Lead data architecture across ingestion, transformation, storage, and serving layers while implementing testing, CI/CD, observability, quality, lineage, governance, and access controls. Integrate restaurant and enterprise data sources, optimize platform performance and cost, deliver production-ready datasets for BI and AI, mentor engineers, and collaborate with cross-functional technical stakeholders.