Top Data & Analytics Jobs in Dallas, TX

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.

Summer 2027 data internship supporting data collection, cleansing, validation, reporting, dashboard development, visualization, predictive analytics, and data security initiatives. The intern will analyze hospitality data related to bookings, customer feedback, operations, and revenue management; collaborate with cross-functional teams; assist with data-tool training; and help maintain compliance with privacy and corporate policies. The role is a 10-week, onsite internship in Irving, Texas.

Supports the IT Enterprise Data team by developing reports and Power BI dashboards, performing data analysis, creating Microsoft Data Factory integrations, and maintaining data warehouse reporting requirements. The intern also assists with data integrity and normalization, software testing and implementation, report generation, and agile scrum activities while collaborating with data managers and the data director.

Develop and maintain SSRS reports, Power BI dashboards, and web applications supporting trust accounting platforms. Write and optimize complex T-SQL, stored procedures, views, and functions; work with data warehouses and OLTP systems; and ensure reporting accuracy and data integrity. Collaborate with business analysts, QA, DBAs, operations, and stakeholders through requirements gathering, testing, deployment, documentation, and user support. Use modern web frameworks, Git workflows, and AI-assisted development tools in a regulated financial services environment.

Supports consumer insights, market sizing, segmentation, sales trend analysis, competitive research, and ad hoc analytics projects. The intern analyzes customer, survey, interview, and sales data; develops reports and presentations; and translates findings into recommendations for marketing, strategy, distribution, and product teams. This is a 10-week paid, primarily onsite internship for an undergraduate student.

Design, build, test and support batch and streaming data pipelines and curated datasets on a modern Lakehouse and AI data platform. Responsibilities include data modelling, optimisation, quality controls, reconciliation, platform tooling, and partnering with stakeholders to deliver reliable, production-ready data products.

Analyze multi-channel fraud trends, develop data-driven insights and recommendations to prevent and detect fraud, evaluate controls and authentication strategies, support testing and implementation of fraud controls, and present executive-ready analytics to inform enterprise fraud strategy and prioritization.

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.