Top Data Engineer Jobs in Tulsa, OK

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.

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.

As a Data Engineer, you'll lead data engineering projects, develop data transformations, build workflows with Apache Airflow, and ensure data quality and integrity while collaborating with stakeholders.

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.

The Data Engineer will build and maintain data pipelines, optimize workflows, manage infrastructure, and enhance pipeline observability while collaborating with teams for effective data delivery.

Design, build, and optimize BigQuery-based data solutions and data models. Manage data storage, partitioning, clustering, ETL, and data quality. Collaborate with architects, data scientists, and engineers to deliver scalable, secure cloud data infrastructure and documentation; senior hires provide technical leadership, code review, and process improvement.

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.

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, and maintain scalable AWS-based data pipelines and storage (S3, Redshift, RDS, DynamoDB). Implement IaC (CloudFormation/CDK), ETL optimization, monitoring, security (IAM, OWASP/CIS best practices), and CI/CD/code pipeline controls. Collaborate with product teams, document solutions, and provide training to support analytics and reliable data infrastructure.

The Data Engineer will develop and maintain data pipelines, perform backend integrations, and enhance data systems for effective reporting and analytics.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

The Principal Data Engineer will lead data architecture initiatives, design scalable data systems, and oversee data standards across teams while ensuring high-quality data infrastructure and guiding engineering teams.

The Data Engineer III will lead the development and maintenance of data infrastructure and tools, ensuring data integrity while driving strategic data initiatives.

Design, build, and maintain an internal data platform and pipelines. Ensure secure, governed, resilient data access for engineering and BI teams. Partner with architects, implement automations, support platform consumption, mentor users, and drive continuous improvement and compliance.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

As a Data Engineer, you will build and maintain data pipelines, ensure data quality, support ML workflows, and optimize query performance using various technologies.

As a Data Engineer, you will design and maintain data pipelines, support DoD systems, and ensure data quality and compliance.

The role involves designing and optimizing data pipelines in Snowflake, developing ETL workflows, collaborating on data integration, ensuring data security, and performance monitoring.

The Data Engineer is responsible for designing data workflows and pipelines, implementing systems engineering principles, and deploying data streaming technologies while ensuring compliance with industry regulations and best practices.

Forward-deployed senior data engineer who deploys, hardens, integrates, and operates a data platform (lakehouse, streaming, governance) in DoD environments. Build pipelines across classification boundaries, produce accreditation evidence (STIG/cATO/FIPS), run day-2 operations, train mission teams, and mentor junior FDEs while feeding field feedback into product improvements.

As a Data Engineer, you will build and maintain data pipelines, convert data into metrics, and operate the platform on AWS. Responsibilities include writing production code, processing data from APIs, and enhancing the orchestration layer using Dagster, while ensuring compliance in a HIPAA-regulated environment.

As a Senior Forward Deployed Data Engineer, you will design and implement data pipelines for media agency clients, manage technical delivery, and ensure data security while mentoring junior engineers and communicating effectively with stakeholders.

The Data Engineer will design and maintain data pipelines, enhance the data warehouse, support machine learning applications, and collaborate with various teams to leverage data effectively.