Top Data & Analytics Jobs in Dallas, TX

Design, build, and maintain scalable cloud-native data pipelines, microservices, and platforms to support real-time and batch processing. Collaborate with architects and stakeholders to translate requirements, implement AWS-based ingestion/streaming solutions, enforce data quality/testing, and operate observability and CI/CD practices to ensure reliable production data systems for autonomy initiatives.

Coordinates forecasting and analysis for workforce management and operations. Develops 6–36-month demand and workforce forecasts, predictive and scenario-based models, variance analyses, and ROI assessments. Translates forecasts into staffing and skill-mix requirements, supports workforce planning strategies, ensures data quality, and presents assumptions, risks, and insights to executives. Partners with workforce management, operations, healthcare management, and analytics teams to align forecasts with business plans.

Develops and maintains business intelligence applications, reports, and SQL-based data solutions. Analyzes requirements, builds and tests complex system components, connects operational data sources, tunes queries, and supports data warehouse integrity. Collaborates with technical and business teams, manages small projects, mentors colleagues, provides training, and serves as a subject matter expert for BI applications.

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.

Designs, builds, tests, and supports enterprise data pipelines for acquired-company system integration and Snowflake archival. Translates business and technical requirements into mappings, transformations, quality controls, monitoring, and deployment plans. Collaborates with architecture, security, infrastructure, application, business, and vendor teams to deliver governed, reusable data solutions. Supports migration, cutover, validation, documentation, hypercare, and operational handoff while improving automation, performance, cost efficiency, and data observability.

Designs and implements governed enterprise data pipelines supporting acquisitions, system integration, archival, reporting, analytics, and compliance. The role uses Snowflake to build scalable ingestion, transformation, validation, reconciliation, and archival solutions. It partners with architecture, security, infrastructure, application, business, vendor, and M&A teams; creates mappings and documentation; supports migration, cutover, go-live, and hypercare; and leads reusable, secure, observable data engineering practices.

Designs, builds, and operates scalable enterprise data platforms supporting ingestion, processing, storage, governance, analytics, and AI/ML. Responsibilities include developing batch and real-time pipelines, lakehouse and warehouse architectures, orchestration, infrastructure automation, CI/CD, monitoring, security, cost optimization, and observability. The role partners with data, ML, DevOps, security, and application teams, troubleshoots complex platform issues, establishes reusable engineering standards, contributes to architecture strategy, and mentors engineers.

Develops and optimizes enterprise SQL Server solutions, including databases, T-SQL, SSIS ETL packages, SSRS reports, and SSAS analytical models. Translates business requirements into technical designs, performs performance tuning, supports releases and production incidents, monitors data workflows, conducts root cause analysis, and implements permanent fixes. Participates in code reviews, testing, documentation, and on-call production support.

Designs and delivers scalable, low-latency streaming data pipelines using Apache Flink, Confluent Kafka, and Apache Iceberg. Modernizes batch and RDBMS workflows into event-driven architectures, builds lakehouse data structures, ensures data quality, optimizes streaming performance, and integrates ITSM and enterprise systems. The role also leads testing, documentation, delivery lifecycle activities, stakeholder collaboration, CI/CD, operational monitoring, and mentoring of data engineers.

Develop and maintain volume forecasting, capacity planning, resource optimization, simulation, and predictive models for Global Operations. Partner with business units to validate model accuracy, present performance to executives, enhance modeling inputs and processes, and support Model Risk Management compliance. The role requires quantitative analysis, time-series modeling, optimization, statistical software, Excel, communication, and collaboration skills.

Leads clinical and operational analytics operations, overseeing analytics teams, capacity planning, quality, delivery performance, and cross-functional alignment. Translates complex healthcare data into actionable insights that support client value, retention, performance improvement, and measurable outcomes. Partners with leadership across data, technology, consulting, research, marketing, sales, finance, and operations while developing analytics talent and improving delivery capabilities.

Participates in a 12-month new-graduate development program while designing, building, deploying, and operating data architectures and pipelines. Develops processes for capturing, transforming, storing, and maintaining structured and unstructured data across distributed and local systems. Applies automation, big-data, artificial intelligence, and machine-learning techniques to support data integrity, compatibility, and evolving business requirements.

Analyzes and corrects claims data errors, investigates root causes, evaluates business impact, and recommends long-term data quality improvements. The role manages claims corrections using business rules, resolves exceptions across systems, collaborates with claims administrators, programmers, vendors, and business teams, and produces ad hoc reports. Strong SQL skills and insurance claims knowledge are required; Snowflake experience is preferred.