Top Senior Data & Analytics Jobs in Dallas, TX

Lead enterprise data architecture strategy and modernization across Microsoft Fabric, Azure, OneLake, lakehouses, warehouses, and integration platforms. Establish standards for modeling, ETL/ELT, governance, security, metadata, lineage, and data quality. Define AI-ready architecture patterns, lead architecture reviews, mentor engineers, and create reusable reference architectures. Drive migration from legacy platforms to Microsoft Fabric while promoting specification-driven development and scalable analytics, reporting, operational intelligence, and AI capabilities.

Design and maintain scalable cloud data pipelines, ELT/ETL workflows, data models, ingestion frameworks, and automation systems supporting cloud cost visibility and optimization. Optimize performance, reliability, and cost across AWS, Snowflake, and related platforms. Ensure data quality, validation, auditability, and production troubleshooting while partnering with Engineering and Finance stakeholders on usage-based insights and cost-aware decisions.

Senior BI Engineer supporting Pharmacy Services Finance Intelligence by analyzing financial data, identifying trends and risks, and delivering decision-ready insights to CFO stakeholders. The role develops semantic-layer data sources, integrates disparate datasets, partners on analytics product delivery, improves solution quality and automation, explores AI-enabled analytics, and mentors junior analysts. Advanced SQL, analytics programming, visualization, statistical modeling, data engineering, communication, and large-scale analytics leadership are central to the position.

Build and scale data infrastructure supporting utility billing reports, analytics, AI-ready retrieval, dimensional models, and customer-facing data products. Responsibilities include developing ingestion and transformation pipelines, creating facts and dimensions, implementing testing and observability, monitoring freshness and lineage, and partnering with engineering, product, compliance, and analytics teams.

Develops and maintains product taxonomy navigation for a global electronics catalog. Reviews industry, competitor, supplier, website metric, and customer behavior data to optimize product hierarchies. Establishes taxonomy procedures, evaluates product placement, and supports data integrity and quality-rule development. Collaborates with product operations, search, analytics, syndication, and management stakeholders to ensure accurate, relevant product data worldwide.

Provides technical leadership for enterprise data platform engineering. Designs and implements ETL, ELT, streaming ingestion, data models, cloud data lakes and warehouses, monitoring, data quality, governance, testing, version control, and CI/CD practices. Leads AWS, Snowflake, and dbt implementations while integrating disparate data sources for analysts and data scientists. Partners with business stakeholders to align data products with organizational strategy and enables self-service analytics and automation.

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.

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.

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.