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Job Summary Serve as a senior engineer in execution systems designing and optimizing AVEVA PI Historian based data solutions that support manufacturing and supply chain operations in a hybrid work model. Collaborate with cross functional teams to deliver reliable real time data enhance operational visibility and drive continuous improvement for global enterprise environments. Responsibilities Develop and maintain the manufacturing data infrastructure including data acquisition and storage Design and implement data acquisition strategies to capture real time manufacturing data from various sources including process equipment instruments IOT and control systems such as MES BMS DCS OEM Develop and maintain data models templates and calculations within the AVEVA PI system to support manufacturing analytics and reporting Collaborate with cross functional teams to define data requirements and implement solutions to address business needs Ensure data integrity and consistency by implementing data quality control measures and monitoring data validation processes Collaborate within Automation Infra team to manage system upgrades patches and performance optimizations for the AVEVA PI system Provide technical support and training to end users on data acquisition tools AVEVA PI system functionalities and data visualization tools Stay up to date with industry trends emerging technologies and regulatory requirements related to data engineering and manufacturing systems Contribute to continuous improvement initiatives identifying opportunities to enhance data management processes system performance and user experience Essential Skills Extensive experience working with the AVEVA PI system ideally within the pharmaceutical industry Understanding of pharmaceutical manufacturing processes including batch processing equipment automation and data acquisition systems Proficiency in data engineering concepts data integration and data management best practices Ability to multitask manage multiple projects and prioritize tasks in a busy environment Nice To Have Skills Previous experience with data visualization and reporting tools such as Tableau Power BI Experience with programming languages such as Python and SQL and scripting is advantageous Knowledge of regulatory requirements such as FDA and GMP related to data integrity and computerized systems validation Previous experience with data Ops tools such as Ignition Highbyte Qualifications Bachelor degree in engineering computer science or a related field Formal training on PI system nice to have
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.