Top Senior Data Engineer Jobs in Dallas, TX

Lead design and implementation of large-scale data pipelines, ETL, and warehousing. Build and manage databases, ensure data quality/security, collaborate with analysts and scientists, evaluate new technologies, mentor junior engineers, and manage project delivery.

Consult with business units to design, develop, and deploy high-quality data solutions. Query and process large datasets, integrate data into big-data systems, mentor engineers, perform quality testing, and collaborate closely with stakeholders in an Agile environment using SQL, Python, Spark, and cloud technologies (preferably AWS).

Design, build, and maintain scalable batch and real-time data pipelines and cloud-native data platforms. Lead data architecture, ETL/ELT workflows, data modeling, performance optimization, metadata and governance, automated testing, CI/CD, and operational runbooks while collaborating with cross-functional teams in an Agile environment to support analytics and ML initiatives.

Design, build, and operate large-scale Hadoop-based data pipelines and streaming systems. Optimize Spark/MapReduce jobs, implement data models and governance, automate orchestration, monitor pipelines, collaborate with data scientists, and mentor junior engineers.

Design, build, and maintain scalable cloud-native data pipelines, microservices, and AI-driven orchestration. Develop Python APIs (Flask/FastAPI), implement advanced SQL transformations (BigQuery), integrate LLMs/agents for automated workflows, and collaborate with Data Science and Product to deliver production-grade, observable, and secure AI-enabled data solutions.

The Data Engineer role involves developing and maintaining data pipelines for forecasting in commercial real estate, ensuring data integrity and supporting analytics teams.

Design and execute end-to-end SAP S/4HANA data migrations: extract, transform, cleanse, validate, reconcile and load data using LTMC, SLT, and LVM. Manage replication, system refreshes, performance tuning, mock migrations, cutover runbooks, and collaborate with functional teams to ensure data governance, auditability, and supportability.

As a Sr Data Engineer, you'll conduct feasibility analyses, develop applications, monitor processes, consult with users, and ensure compliance while serving as a mentor to junior analysts.

The Senior Consultant - Data Engineer will build scalable data systems, manage data pipelines, and enhance data lifecycle processes to drive business decisions.

Design, build, test, and maintain scalable batch and real-time data pipelines and applications. Ensure production readiness, reliability, security, and performance. Drive DevOps/DataOps practices, troubleshooting, monitoring, and continuous improvement. Collaborate with product, architecture, engineering, and business stakeholders to translate requirements into technical designs and deliver data products supporting analytics and AI use cases.

Lead data engineering efforts within Identity and Access Management to design, build, and deploy cloud-native data solutions on AWS, automate integrations, implement database management and CI/CD, mentor engineers, and improve operational efficiency and user experience.

Design, build and deliver SAP-originated and non‑SAP data in formats consumable by non‑SAP tools and external B2B partners using SAP BO/Data Services, BW/BI. Support ETL, integration and data delivery processes.

Lead design, build, and optimization of the enterprise data warehouse and production data pipelines. Own platform architecture, integrate legacy systems (AS400), support Power BI semantic models (DAX), implement monitoring, CI/CD and governance, and mentor engineers to transition from consultant-run platforms to an internally managed, scalable data ecosystem.

The Senior Data Engineer will design and maintain data pipelines, ensuring data reliability and consistent models, while collaborating with stakeholders to improve data practices.

Design, build, and maintain scalable semantic 360 data models and transformation pipelines. Implement cleansing, enrichment, business rules, KPIs, and scoring algorithms using SQL and Python/Scala. Employ AI coding assistants and modern AI engineering practices to accelerate development while ensuring traceability, data quality, performance, and alignment with product and analytics needs.

Lead and architect high-performance SQL Server VLDB solutions (SQL Server 2019+). Own performance tuning, ETL/data loading (SSIS/SSAS), data modeling, security (TDE/entitlements), code reviews, AI-assisted optimization, mentor teams, and manage delivery of scalable data warehouse pipelines.

Lead design and development of data solutions, translate business needs into code, query and process large datasets, mentor engineers, perform quality testing, collaborate with stakeholders, and support Agile delivery.

Design, build, and maintain scalable, high-performance data pipelines, ingestion, transformation, and data export solutions. Implement data quality, testing, and monitoring, collaborate with product and stakeholders to build analytical data models, support production jobs, perform PoCs, and contribute to roadmap, standards, and documentation.

Design and build scalable, semantically consistent 360 entity data models and transformation pipelines. Implement cleansing, enrichment, KPIs, scoring, and business rules in SQL and Python/Scala, ensure data quality, lineage, and performance at scale. Use AI coding assistants and SDD to accelerate development, create tests and documentation, and collaborate with domain experts, data scientists, and product teams to deliver trusted, reusable data assets.

The Data Engineer will optimize data infrastructure, modernize SQL processes, support data governance, and mentor team members while enhancing analytics capabilities.

Senior Data Modeler responsible for designing logical and physical data models, implementing database designs, planning data collection/cleansing, coordinating documentation, and partnering with data transformation teams to enable ETL/ELT pipelines, hybrid on-prem/cloud data movement, and reporting solutions.

The Data Integration & Pipeline Engineer will build and maintain ETL/ELT pipelines, ensuring efficient data flow, quality, and performance across platforms.

Design and build scalable Microsoft Fabric pipelines and lakehouse models, optimize Power BI semantic models and refresh strategies, enforce SDLC and CI/CD best practices, mentor teammates, and ensure SLA-driven, client-facing analytics reliability and performance.

Lead design, maintenance, and optimization of on-prem and cloud data platforms. Perform DBA duties for SQL Server, manage HA/DR and replication, troubleshoot performance, lead on-prem to Azure migrations, maintain Azure data services and Microsoft Fabric, optimize cloud cost/performance, implement monitoring, collaborate with architects and BI teams, and mentor junior engineers.

The Senior Data Developer Tech Lead will design and manage scalable data solutions within Hadoop, lead streaming data architecture, optimize performance, and integrate AI/ML capabilities, while coaching team members and ensuring best practices in the banking domain.