Top Analysis Reporting Jobs in Dallas, TX

Designs and engineers scalable Azure and Databricks Lakehouse data platforms, including ingestion frameworks, batch and streaming pipelines, governed Bronze-to-Gold data models, quality controls, semantic layers, CI/CD, Infrastructure as Code, and access policies. The role translates enterprise architecture into reusable engineering solutions, guides delivery teams, troubleshoots technical issues, and partners with business stakeholders and data stewards to define metrics, requirements, and governance standards.

Designs and leads scalable Azure and Databricks Lakehouse data engineering solutions. Builds governed batch and streaming pipelines, Bronze-to-Silver transformations, curated Gold-layer models, semantic-layer integrations, CI/CD automation, and Infrastructure as Code. Establishes data quality, metadata, security, and Unity Catalog standards while optimizing performance and cost. Guides delivery teams through architecture, onboarding, debugging, and design reviews, and partners with business stakeholders and data stewards to define requirements and validate metrics.

Build and scale a client-facing analytics platform using Microsoft Fabric, scalable pipelines, Lakehouse architectures, dimensional models, and Power BI semantic models. Establish ingestion, observability, testing, CI/CD, and SDLC standards while optimizing performance, refresh strategies, costs, and SLAs. Lead architecture decisions, communicate technical concepts to business stakeholders, mentor engineers, and proactively manage platform risks in a client-facing analytics environment.

Lead competitive and market intelligence research to generate actionable, leadership-ready insights that inform client development, go-to-market strategy, and firm priorities. Synthesize financial, transactional, regulatory, and market data into strategic recommendations; produce briefings, benchmarking, and visualizations; improve intelligence tools and workflows; and partner with Marketing & Client Development to support pitches, cross-selling, and growth initiatives.

Leads the strategic direction of performance analytics and measurement for global enablement efforts. Owns the analytics roadmap, defines KPIs, develops AI-driven seller-readiness assessments, and partners with data engineering, sales, enablement, and technology teams. Translates complex analysis into executive-level insights, drives cross-functional alignment, and leads strategic measurement initiatives.

Develops statistical, optimization, simulation, forecasting, and predictive models to solve complex business problems. Analyzes operational, supply chain, financial, and business data; performs scenario planning; creates dashboards and reports; and translates findings into recommendations. Partners with cross-functional teams on network optimization, demand planning, cost reduction, supplier performance, and operational efficiency initiatives. Communicates analytical insights to management and supports implementation of data-driven solutions.

Analyzes and improves third-party financial data flows across wealth management providers, feeds, intermediaries, and enterprise platforms. Responsibilities include source documentation, data profiling, reconciliation, lineage mapping, root-cause analysis, provider engagement, scorecards, and remediation tracking. The role translates complex technical findings into business recommendations, develops scalable data-quality standards and automation, and serves as a subject matter expert across data, operations, architecture, engineering, and external partners.

Leads data management for the Supervision and Regulation Common Data Platform, overseeing data cataloging, access management, records management, taxonomies, data quality, governance, and stakeholder engagement. Develops scalable strategies, supports ABAC implementation, manages risk mitigation and continuous improvement, and mentors data management and project professionals. Communicates with senior Federal Reserve and regulatory leaders while driving adoption, change management, training, and organizational data management initiatives.

Design, build, optimize, and maintain scalable data pipelines and platform components supporting analytics and AI/ML. Own complex engineering initiatives, resolve performance and production issues, improve governance and data models, and contribute to infrastructure as code and CI/CD. Provide technical leadership through architecture guidance, code reviews, mentoring, documentation, and cross-functional collaboration. Support platform modernization across cloud data platforms, warehouses, lakehouses, and streaming or feature-store use cases.

Designs, builds, tests, maintains, and optimizes large-scale data pipelines, ETL processes, ingestion workflows, and cloud data storage. Develops Databricks data engineering and AI/ML pipelines, Azure Data Lake solutions, Power BI dashboards, and CI/CD automation. Ensures data quality, security, scalability, cost efficiency, and reusable engineering practices while collaborating with distributed technical teams.