Top Senior Analysis Reporting Jobs in Dallas, TX

Manage client data, analytics, and AI managed-services workstreams. Develop data pipelines, dashboards, reporting, and analytics outputs; remediate data-quality issues; tune AI models and platform components; and improve data operations, observability, and reporting workflows. Collaborate with clients to translate business needs into data solutions, interpret insights, review deliverables, and mentor junior team members.

Leads client managed services engagements involving data, analytics, and AI operations. Oversees project planning, budgets, timelines, data quality, master data management, pipelines, platform maintenance, model tuning, and performance monitoring. Translates business requirements into data solutions, reviews deliverables, manages risks, and coaches team members while promoting AI-enabled automation and adherence to professional standards.

Owns data strategy, governance, quality, protection, documentation, and delivery for a credit card product. Partners with business, analytics, technology, risk, and operations teams to define data requirements, deploy data solutions, manage workstreams and KPIs, mitigate data risks, and ensure compliance with firmwide standards. Leads direct or matrixed staff and provides subject matter expertise across data management, engineering, architecture, pipelines, modeling, and analytics.

Deliver analytics and insights for the ~$100B Commercial Term Lending portfolio. Develop data solutions to source, combine, and transform data; monitor portfolio performance and market trends; build scalable dashboards and self-service reporting; partner with Controls and Compliance; and support special projects and ad hoc analyses to inform risk and portfolio strategy.

Analyzes complex data to support business strategies, develops business intelligence tools, dashboards, metrics, and self-service data solutions, and manages data quality, metadata, lineage, definitions, security, and access governance. The role uses Python, R, Spark, SQL, AWS, and data visualization technologies while partnering with business and technical teams to deliver insights and monitor data quality.

Leads enterprise data engineering strategy, architecture, modernization, and governance. Designs scalable cloud-native data lakes, warehouses, lakehouses, ingestion pipelines, and real-time processing platforms. Establishes standards for data modeling, security, quality, observability, DataOps, DevOps, and compliance. Provides technical leadership across engineering teams, mentors senior professionals, drives transformation programs, and partners with business and technology stakeholders to deliver resilient data products supporting analytics, regulatory reporting, and operational intelligence.

Maintains enterprise Snowflake data lake, warehouse, and mart infrastructure; manages access, onboarding, training, ingestion workflows, and platform configuration. Provides daily technical support to global developers, resolves data and query issues, develops SQL solutions, and uses Python for automation. Translates factory business processes into technical requirements and documentation, evaluates Snowflake capabilities, and guides data products through production delivery.

Leads enterprise data architecture initiatives by translating business requirements into scalable data designs, assessing impacts across systems and pipelines, modernizing legacy environments, and guiding AI/ML data solutions. Partners with data leaders and stakeholders, manages project plans, monitors implementation progress, and communicates risks and mitigation plans. Requires expertise in cloud and hybrid environments, data platforms, data engineering or architecture, and team or project management.

Develop global engagement strategies for Crunchyroll’s streaming platform using consumer behavior, audience segmentation, experimentation, and analytics. Analyze viewing journeys, engagement barriers, churn signals, and lifecycle interventions. Build measurement frameworks, define success metrics, evaluate A/B tests, and identify strategies that strengthen viewing habits and retention. Partner with Product, Data Science, Lifecycle, Curation, and Consumer Insights teams to translate complex behavioral data into executive-level recommendations and prioritized initiatives.

Designs, builds, and maintains secure data pipelines, ETL processes, data warehouses, and quality controls. Collects, validates, cleanses, and analyzes data; develops SQL queries, Tableau dashboards, and AWS-based solutions; investigates data integrity issues; documents standards; and partners with stakeholders to deliver technical solutions using Agile and DevOps practices.

Leads end-to-end data enablement for Supply Chain and Manufacturing domains. Partners with business and technical stakeholders to define use cases, roadmaps, data models, semantic layers, integration requirements, quality controls, and governed data products. Builds and optimizes Databricks lakehouse pipelines using SQL, Python, PySpark, and Delta Lake across complex ERP, manufacturing, procurement, inventory, and finance systems. Establishes standards for lineage, security, documentation, reliability, and production readiness.

As a Pricing and Revenue Planner, you will manage pricing analytics, forecasting, synthesizing data into actionable insights, and collaborating with various teams to drive revenue improvements and profitability analysis.