Sr Lead Data Systems Engineering

About GlobalFoundries: GlobalFoundries is a leading full-service semiconductor foundry providing a unique combination of design, development, and fabrication services to some of the world's most inspired technology companies. With a global manufacturing footprint spanning three continents, GlobalFoundries makes possible the technologies and systems that transform industries and give customers the power to shape their markets. For more information, visit www.gf.com. Summary of Role: The Data Solutions Group is responsible for integrating manufacturing and engineering data out of a high variety of source systems used in the semiconductor engineering and production process. The data warehouse solutions are used in the GLOBALFOUNDRIES Fabs in Dresden, in the US and in Singapore, and the Data Solutions Group is responsible to conceptualize and provide timely, high-quality solutions that address analysis needs of engineers in a leading-edge semiconductor foundry Essential Responsibilities: Senior data engineering professional with strong technical solution design expertise, responsible for designing, building, optimizing, and governing enterprise data infrastructure and data pipelines. The role works closely with the Data Product Design team to translate business and design requirements into scalable, secure, and maintainable technical data products, while providing technical leadership and guidance to engineering and support teams. Other Responsibilities: Perform all activities in a safe and responsible manner and support all Environmental, Health, Safety & Security requirements and programs. Responsibilities include: Leading complex, cross-functional data engineering projects, acting as a subject matter expert for Ab Initio, data warehouse design, ETL architecture, and cloud data platform integration. Building data Solution: Creating secure, stable, and scalable data pipelines, managing analytics platforms Design Standards and Framework: Provides appropriate consulting, interfacing, standards and framework for data pipelines, Mentoring junior and mid-level data engineers, guiding implementation partners and operations support teams, reviewing design and code quality, and recommending engineering best practices. Evaluating access control: Evaluating and reporting on access control processes to determine data asset security Developing documentation: Creating technical documentation that supports best practices Required Qualification: Experience in preparing Data warehouse design artifacts based on given requirements - Defining Standards, Building Frameworks, and Source-Target Mapping Strong analytical and data modeling skills including logical and physical schema design Deep understanding of database technology and data use within analytic platforms Hands-on expertise in Ab Initio GDE, Co>Operating System, EME, Conduct>It, Express>It, DML, XFR, multifile systems, and graph parameterization for enterprise-scale ETL development and support. Experience owning production data pipelines, including incident triage, SLA management, root cause analysis, job recovery, restartability, scheduling coordination, and operational handoff to support teams. Experience with AWS cloud Services including EMR, Redshift/Postgres Experience with other cloud and ETL technologies, including Databricks, Snowflake, and Ab Initio. Good Understanding of other programming languages Python, Java Proven experience with large, complex database projects in environments producing high-volume data Strong understanding of data governance practices, including metadata management, lineage, auditability, access control, data retention, and secure handling of sensitive enterprise data. Demonstrated Problem solving skills; familiarity with various root cause analysis methods; experience in documenting identified problems and determined resolutions. Experience analyzing performance issues and tuning large-scale data pipelines, SQL workloads, ETL graphs, and dat base processe