Data Engineer Jobs in Plano, TX

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.

Design, build, and maintain scalable data pipelines and applications on AWS and Databricks. Develop production-quality Python code, process large datasets with Spark, implement IaC CI/CD with Terraform, and apply AI-assisted development responsibly. Troubleshoot data workflows, create architecture artifacts, and contribute to engineering best practices and team collaboration.

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.

Design, develop, test, implement, and support cloud-based data solutions. Lead and mentor engineering teams, build distributed and streaming data pipelines, optimize performance, and collaborate with product managers to deliver scalable data platforms.

Lead the design and delivery of cloud-based DLP platform services that centralize policy authoring, routing/scoring of findings, and enforcement. Collaborate with product, security, and policy teams; drive architecture, data modeling, event design, deployment automation, and regulatory-compliant, auditable outputs. Mentor engineers and contribute to operational strategy and production validation.

Design, build, and maintain secure data pipelines for structured and unstructured sources. Segment and protect data domains, enforce access controls and classification, and enable analytics/AI use cases. Optimize workflows for performance, observability, and resiliency across cloud and hybrid platforms. Partner with stakeholders to translate compliance and business needs into reusable, governed data solutions and support production systems with strong attention to integrity, lineage, and auditability.

Lead design and build scalable, low-latency, fault-tolerant streaming data platforms and distributed data pipelines. Own streaming analytics, cloud-based data stores, CI/CD practices, and mentor engineers while collaborating with product, security, and ML teams to deliver robust cloud solutions.

Design, build, test, and operationalize complex data pipelines and multi-layer data architectures using Snowflake and dbt. Analyze source systems, perform data mapping and transformations, ensure data governance, quality, and security, resolve defects, optimize query and pipeline performance, and collaborate with engineering and business teams to support BI and AI/ML use cases.

Design, build, and maintain data pipelines and ETL processes to support analytics and reporting. Implement and optimize Snowflake data warehousing, Matillion ETL, and data quality/validation. Write and tune complex SQL, develop Tableau dashboards, troubleshoot data issues, document architectures, and collaborate with cross-functional teams to deliver governed, audit-ready data solutions.

Lead design and build scalable, low-latency, fault-tolerant data platforms and pipelines. Mentor engineers, influence data architecture and governance, build analytics stores using big-data and cloud technologies, collaborate with product and security teams, and ensure CI/CD, resiliency, testing, and performance for data-driven solutions.

Lead Software Engineer responsible for designing, building, and maintaining scalable data pipelines and platform components (cataloging, quality, lineage, governance). Implements data modeling, partners with stakeholders to deliver production-grade code, automates operations, evaluates vendors, and leads Agentic Autonomous Lakehouse and engineering communities to drive platform innovation and operational stability.

As a Lead Data Engineer, you will design and develop solutions, collaborate with teams on data technologies, and support cloud-based data warehousing and big data applications.

Lead design and build scalable data processing and control-plane solutions on Databricks/AWS. Develop Python/PySpark/SQL pipelines, APIs/SDKs, governance, observability, CI/CD, and operational runbooks. Mentor engineers, drive adoption of AI-assisted development, and ensure data quality, security, lineage, and platform reliability.

Lead development and operation of scalable ETL/data transformation pipelines using Spark and data lake technologies. Design, automate, monitor production workflows, improve cost and reliability, mentor junior engineers, and contribute to platform/SDK infrastructure and CI/CD while enforcing secure, AI-assisted engineering practices.

As a Lead Data Engineer, you'll lead the design and implementation of scalable data platforms, build distributed streaming data pipelines, and collaborate on technical solutions using big data technologies and agile methodologies.

Lead engineer responsible for designing, building and operating scalable Big Data/ETL pipelines and production services on AWS. Drive automation (including LLMs/agents), SRE practices, security and data accountability, monitoring/alerting, incident management, and cross-team coordination. Champion AI-assisted engineering, remediate control/security findings, and improve reliability, performance, and operational efficiency.

Lead design and deliver enterprise data governance: implement data models, metadata standards, data cataloging/lineage, governed ETL/ELT pipelines, data quality controls, and coach teams on AI-assisted engineering and secure practices.

Lead design and deliver AI-enabled data platform capabilities (metadata, lineage, data quality, retention). Drive adoption of enterprise-authorized AI-assisted engineering, build agentic production systems, develop secure production code, automate remediation, establish production SRE controls, and mentor teams on responsible AI and validation standards.

Lead Data Engineer responsible for designing, developing, testing, and supporting cloud-based data solutions. Collaborate across Agile teams, mentor engineers, build distributed and streaming data systems, and optimize performance using big data technologies and data warehouses.

Design and maintain scalable ETL/ELT pipelines, develop data solutions using Databricks and Snowflake, and collaborate with cross-functional teams to ensure data quality and performance optimization.

The Lead Data Engineer will design, develop, and support complex technical solutions using Java, Python, AWS, and big data technologies. Responsibilities include collaborating with Agile teams, mentoring, and delivering cloud-based solutions.

Design, build, and maintain cloud-native ETL/data pipelines and integrations using AWS Glue, Java or Python. Deploy and optimize containerized applications on Amazon ECS, maintain CI/CD (Jenkins, Docker, Git), and support production incidents. Analyze large datasets to inform business decisions and collaborate with stakeholders to translate requirements into technical solutions.

Lead design and implement secure AWS Data Lake solutions, develop IaC and application code, promote AI-assisted engineering practices, analyze large datasets, collaborate across teams, and drive secure, scalable software delivery and improvements.

Lead an agile engineering team to design, develop, and operate secure, scalable applications. Provide technical guidance, write and review production code, drive AI-assisted engineering adoption, influence product design, and promote firmwide SDLC practices using cloud-native, microservices, and Big Data technologies.

Lead an agile team to design, build, deploy, and operate cloud-native data and ML platforms. Provide technical guidance, write and review secure production code, drive AI-assisted engineering adoption, migrate legacy big-data apps to cloud, build data pipelines and monitoring/provisioning tools, and influence architecture and automation across the SDLC.