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.

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.

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.

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.

Supports the development and maintenance of data pipelines, ETL/ELT workflows, data models, schemas, and databases. Performs data cleaning, validation, quality checks, monitoring, troubleshooting, documentation, and testing. Collaborates with data engineers and business teams while gaining experience with Python, SQL, Spark, cloud platforms, machine learning pipelines, big data processing, and data architecture.

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.

Build and maintain BI reports, dashboards, visualizations, audience segments, and analytics solutions for convenience retail, petroleum, and mobile payment customers. Translate customer needs into requirements, prepare and validate data using SQL, support CRM campaigns, analyze program performance, troubleshoot data issues, and optimize BI solutions on Azure. Collaborate with marketing, CRM, technical teams, project managers, and customers while documenting and testing delivered solutions.

Designs and develops system-level workforce intelligence across the employee lifecycle. Identifies workforce trends, integrates HR insights with finance and operational metrics, creates executive-ready reporting and narratives, and supports strategic planning. Partners with data product owners and cross-functional stakeholders to align workforce intelligence with Federal Reserve System priorities and HR product strategy.