Sr Lead Data Systems Engineering

GlobalFoundries•Austin, TX

About The Position

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.

Requirements

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 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.

Nice To Haves

Master’s degree in information technology, Electrical Engineering or similar relevant fields.
Very good knowledge of data warehouse architecture approaches and trends, and high interest to apply and further develop that knowledge, including understanding of Dimensional Modelling and ERD design approaches.
Experience in developing streaming applications Spark Streaming, Flink, Storm, etc.
Excellent conceptual abilities compared with very good technical documentation skills, e.g. ability to understand and document complex data flows as part of business / production processes.
Familiarity with SDLC concepts and processes.
Experience in semiconductor / High Tech Manufacturing industry.
Experience with reporting data solutions and business intelligence tools.
Knowledge of statistical data analysis and data mining.
Experience in test management, test case definition and test processes.

Responsibilities

Designing, building, optimizing, and governing enterprise data infrastructure and data pipelines.
Translating business and design requirements into scalable, secure, and maintainable technical data products.
Providing technical leadership and guidance to engineering and support teams.
Performing all activities in a safe and responsible manner and supporting all Environmental, Health, Safety & Security requirements and programs.
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 secure, stable, and scalable data pipelines, managing analytics platforms.
Providing 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 and reporting on access control processes to determine data asset security.
Creating technical documentation that supports best practices.
Owning production data pipelines, including incident triage, SLA management, root cause analysis, job recovery, restartability, scheduling coordination, and operational handoff to support teams.
Analyzing performance issues and tuning large-scale data pipelines, SQL workloads, ETL graphs, and database processes.