Sr Data Product Engineer

Introduction: The Data Engineering and Analytics Group is responsible for integrating manufacturing and enterprise data out of a high variety of source systems used in the semiconductor engineering and production process. The data solutions are used in GLOBALFOUNDRIES Fabs in Dresden, in the US and in Singapore and also other wordwide locations. The DEA team is responsible to design and build data products end-to-end, meeting business team requirements. It does so by improving data architecture, by solutioning, building and providing timely, high-quality solutions that address analytical needs of engineers in a leading-edge semiconductor foundry.

Your Job

• Understand the business case and translate to a holistic solution involving AWS Cloud Services , PySpark, EMR, Python, Data Ingestion and Cloud DB Redshift / Postgres
• PL/SQL development for high volume data sets.
• Proven experience with large, complex database or data lake projects in environments producing high-volume data
• Demonstrated problem solving skills; familiarity with various root cause analysis methods; experience in documenting identified problems and determined resolutions.
• Communication with stakeholders and business partners across all worldwide locations.
• Understanding and aligning business partners across locations doing requirements engineering and business case mapping.
• Leading projects: Working on complex, cross-functional projects, and acting as a subject matter expert
• Designing data platforms: Creating secure, stable, and scalable data collection, storage, access, and analytics platforms
• Developing documentation: Creating functional and technical documentation that supports best practices
• Experience in preparing data warehouse design artifacts based on given requirements (ETL framework design, data modeling, source-target-mapping),
• Interaction with Data Governance teams – aligning on data models, lineage and relationships.
• Data Analysis & Engineering for data aggregation and curation
• Interfacing with architecture team, cloud engineering teams and vendors on designing state of the art solutions.
• Makes recommendations regarding enhancements and/or improvements
• Provides appropriate consulting, interfacing, and standards relating to database management, and monitors transaction activity and utilization.
• Performance issues analysis and tuning, optimization opportunities
• Data Warehouse design and development, including logical and physical schema design.

Other Responsibilities:

• Customer/stakeholder focus. Ability to build strong relationships with Application teams, cross functional IT and global/local IT teams – as well as interfacing with vendors (e.g. AWS)
• Advising junior engineers & Build Team: Providing guidance to junior engineers and ETL Build team and BI/Analytics teams

Required Qualifications

• Bachelor or master's degree. Preferably in information technology or electrical engineering – but since job focus on business interaction also background in other fields is welcome.
• Proven experience (10 year minimum) with data engineering, analytics, design and optimization.
• Very good knowledge of data architecture approaches and trends, and high interest to apply and further develop that knowledge, including understanding of OLAP/OLTP, ML, genAI, modelling, statistics.
• Problem solving experience & analytics skills – e.g. with L6S curriculum (green/black belt)
• Good experience in AWS Services, Big data, PySpark, EMR,Python, Cloud DB RedShift
• Proven experience with large, complex data projects in environments producing high-volume data,
• Proficiency in SQL and PL/SQL
• Excellent conceptual abilities pared 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
• Translate business requirements into technical specifications. This involves critical thinking, problem-solving, and the capacity to work with large datasets.

Additional Skill

• Experience using and developing on AWS services, AWS certification, AWS Solutions Architect
• Proficiency in programming languages such as Python, PySpark, SQL, Java, C++ is highly recommended.
• Understanding of machine learning and AI technologies is becoming increasingly important for data architects
• Experience in semiconductor industry,
• Knowledge of Semistructured datasets
• Experience with reporting data solutions and business intelligence tools
• Experience in collecting, structuring and summarizing requirements in a data warehouse environment,
• Knowledge of statistical data analysis and data mining,
• Experience in test management, test case definition and test processes

Preferred Qualifications

• Bachelor's or master's degree with Minimum 7..10 Years Exp
• AWS Cloud Services, PySpark, EMR, Python, Cloud DB Redshift / Postgres and Data Ingestion
• Experience in preparing Data Warehouse design (ETL framework design, data modeling, source-target-mapping)
• Problem Solving methodologies