Senior Data Architect

World Wide Technology is looking for a Data Architect / Data Engineer. This job is part of WWT’s Strategic Resourcing services. The candidate will be supporting a WWT customer and will be employed by one of WWT’s preferred partners. Role: Data Architect / Data Engineer This REMOTE role is 6 month contract with possibility of extension, candidate needs to sit in PST hours. This person needs to be a hands on Engineer with an Architecture background as well. Overview: We are seeking a skilled and versatile Data Architect / Data Engineer to design, build, and optimize data platforms and pipelines within a distributed environment. The ideal candidate will possess deep expertise in managing large-scale data systems, data integration, modern data engineering practices, and pipeline orchestration. You will play a key role in architecting and engineering scalable, high-performance data solutions that drive business insights and innovation. Key Responsibilities: • Design, implement, and manage scalable data architectures on distributed platforms (e.g., MapR, HPE Unified Analytics and Data Fabric). • Develop, optimize, and maintain robust data pipelines using tools such as Spark, Airflow, and EzPresto. • Configure and maintain Kafka architecture, MapR Streams, and related technologies to support real-time and batch data processing. • Implement Change Data Capture (CDC) mechanisms and integrate data using APIs and streaming techniques. • Monitor, tune, and troubleshoot distributed data clusters including MapR and Kubernetes environments. • Develop and maintain CI/CD pipelines using Jenkins and integrate with GitHub for automated testing and deployment. • Collaborate with cross-functional teams to ensure data quality, governance, and compliance standards are met. • Leverage tools such as Iceberg and Superset for data storage optimization and visualization. Required Skills & Experience: • Strong experience with distributed data platforms, including MapR and Kubernetes. • Proficient in data pipeline tools and frameworks: Spark, Airflow, EzPresto. • Solid programming and scripting skills: Python, Bash. • Expertise in Kafka architecture and operations. • Experience with CI/CD development workflows using Jenkins and GitHub. • Knowledge and use of Apache Iceberg for data lake management. • Familiarity with data architecture best practices, including CDC and API-based integrations. Preferred / Nice to Have: • Experience with HPE Unified Analytics and Data Fabric. • Familiarity with MapR Streams and Superset for real-time analytics and dashboarding.