Top Data Engineer Jobs in Dallas, TX

As a Senior Associate in Data Engineering at PwC, you will design and implement data architecture strategies, analyze complex issues, mentor junior members, and build client relationships while ensuring adherence to project standards.

As a Senior Manager in Data Engineering, you will lead teams to design data architectures, develop data solutions, manage client engagements, and ensure compliance with data governance policies.

As a Manager in Managed Services, you'll lead data ecosystems projects, mentor juniors, manage client accounts, and deliver data strategies to optimize operations and drive insights for clients.

Lead data engineering projects, develop and implement data pipelines and architecture strategies, manage data quality, and mentor team members at PwC.

Deliver data engineering and ETL solutions to support client analytics. Build and maintain data pipelines, optimize SQL, design data architecture (star/snowflake models), create BI reports/dashboards, improve data quality, and support client engagements in regulated environments while learning and growing technical and client-facing skills.

The Data Engineer Senior role involves developing data solutions, leading analysis efforts, and designing data service infrastructures within financial services using various technologies.

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, apply data modeling and DAGs, use Databricks, Airflow, and Hadoop, and collaborate with clients to deliver actionable insights.

Senior Data Engineer on PwC's Managed Data, Analytics & Insights team to design, build and manage advanced data ecosystems. Responsibilities include designing data solutions and scalable pipelines, solving complex problems, mentoring junior staff, maintaining high delivery standards, and building client relationships while aligning solutions to business context.

Lead and mentor a data engineering team to design, develop, test, and support cloud-based big data and streaming solutions. Build full-stack data pipelines using Java/Scala/Python, RDBMS/NoSQL, Redshift/Snowflake, and cloud platforms. Collaborate with product managers, perform unit tests and code reviews, and promote engineering best practices and tech community engagement.

Lead and mentor data engineering teams to design, build, test, and support cloud-based, full-stack data solutions. Work with big data, streaming, and data warehousing technologies (Redshift/Snowflake), collaborate with product managers, and ensure high-quality, performant code and systems.

Lead Data Engineer designs, develops, tests, and supports cloud-based data solutions. Collaborates with Agile teams, mentors engineers, implements big data and streaming systems, and optimizes code for performance to deliver data-driven products.

Lead Data Engineer designs, develops, tests, and supports cloud-based data solutions. Collaborates with Agile teams on distributed, real-time, and ML-enabled systems using languages and data platforms (Java, Scala, Python, Go, Redshift, Snowflake). Mentors engineers, performs code reviews and unit tests, and drives technical innovation and experimentation.

Lead design, develop, test, and support cloud-based data platforms and scalable data pipelines. Mentor engineers, collaborate with product managers, and deliver high-performance data lakehouse/warehousing and event-driven solutions using big data and cloud technologies.

Builds and operates scalable batch and real-time data pipelines (Databricks/Spark, Kafka), maintains Customer 360 data model and feature pipelines, ensures data quality/governance, delivers governed customer attributes to activation platforms, and supports privacy/compliance.

Design, develop, and maintain ETL pipelines, databases, and data visualizations to support 300mm semiconductor manufacturing. Analyze operational performance, automate data extraction, troubleshoot systems, collaborate with stakeholders, and integrate emerging technologies to improve manufacturing efficiency.

Lead data engineering efforts within Technology Consulting: design data architecture and pipelines, implement AWS/Redshift and ETL solutions, support BI (QlikView/Oracle BI), coach teams, manage client relationships and SLAs, apply systems thinking to optimize outcomes and validate solutions with stakeholders.

Design, build, and support secure, scalable cloud data solutions and ETL pipelines (PySpark) for regulatory reporting and analytics. Lead technical solution design, implement CI/CD with Azure DevOps, enforce data governance, quality, and compliance, produce documentation, mentor teams, and collaborate with stakeholders to align data architecture with business goals.

Design, build, modernize, and maintain operational and analytical data capabilities for Wealthscape Reporting, Analytics and Insights. Perform solution design, data analysis, ETL development, and production rollouts using Snowflake, AWS, cloud databases, and CI/CD pipelines. Collaborate across teams in a fast-paced financial services environment.

Design, architect, and deliver scalable data pipelines and storage solutions using big data and cloud technologies. Lead technical strategy, mentor engineers, ensure data governance, security, and performance, and collaborate with Data Science and Product teams to support analytics and ML initiatives.

Design, build, and optimize HANA-native data models (calculation views, CDS, AMDP, SQLScript) for S/4HANA, BW/4HANA, and standalone HANA. Lead performance tuning, replication, security, capacity planning, and integration with Fiori, BW, and BTP. Mentor junior engineers and maintain technical documentation and runbooks.

Lead data engineering engagements to design, build, and maintain ETL/ELT pipelines and cloud data architectures. Manage client accounts and mentor teams, leverage tools like DataStage, AWS/Redshift, DB2/SQL Server, GoldenGate, and BI/visualization platforms to deliver analytics, performance tuning, and scalable reporting solutions.

Design, build, test, deploy, and monitor batch and streaming data pipelines and ETL processes. Evaluate and adopt data technologies (including Adobe Experience Platform and CDPs), collaborate with data scientists, architects, and business partners to ingest and prepare large semi-structured/unstructured datasets for ML training, model execution, and search analytics, and implement automation, documentation, and tooling for scalable analytic data systems.

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

Lead and mentor engineering teams to design, build, test, and support cloud-based data platforms and streaming solutions. Implement big data, ETL, and data warehousing using cloud services and distributed tools, collaborate with product managers, and ensure high-quality, performant code.

The Data Engineer will develop data pipelines, ensure data reliability, and support process automation while collaborating within Agile teams.