软件工程师 (Web development/SQL/Python)
Job Title：软件工程师 (Web development/SQL/Python)
The primary mission for this Group is to manage corporate Quality and Compliance programs that enable high-quality product development by defining quality standards, devising measurement techniques, publishing metrics, and managing external quality audits.
The Data Analyst will be the resident-expert in all systems supporting our operations and be the go-to person for data analytics. The person will play a key role in extracting stories from our cumulated data, correlate factors, analyze trends, and enable our product teams to make informed quality decisions.
The candidate will play an essential role in engineering various metrics by devising new measurement/reporting methods to improve scalability and efficiency of our operations. The candidate must play a hands-on role and evolve over time to incorporate new techniques.
The candidate must closely interact with other members of the Corporate Quality Team, as well as numerous groups within the Synopsys Central Engineering organization and IT to instrument our processes by accessing various database that supports our initiatives.
The candidate must have knowledge about various software development models and familiar with software build, regression, quality tools, etc. The candidate must be data-savvy, with a practical knowledge of database and systems. Must also demonstrate experience in managing projects and be self-motivated.
The candidate must have BS/MS with 2+years of relevant experience in Computer Science, or Software Engineering or Math. Must possess excellent written and verbal English communication, ability to manage projects, work independently, and strong collaboration skills.
The candidate must be proficient in software product development, various metrics, database architecture, data analysis tools and techniques, Unix/Windows scripting languages, etc.
Preference will be given to candidate experienced in scripting knowledge (i.e., Python, Perl, etc.), advance knowledge in Excel and other analytical tools (i.e., PowerBI, Lumira, Tableau, Splunk, etc.), Database architecture and tools (SQL, Oracle, SAP Business Intelligence, etc.) and ability to apply Machine Learning (models/algorithms) to improve processes and productivity.