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We are looking for a talented and experienced Data Engineer to join the SPO Data Science team and work at the intersection of data engineering, analytics, automation, and product development. In this role, you will play a key part in building and maintaining the data infrastructure that powers our supply chain planning, inventory optimization, predictive models, and distribution operations. This is an excellent opportunity for someone who is passionate about data, enjoys solving complex business challenges, and wants to build solutions that create a meaningful operational impact. About the Team You will join a dynamic Data Science team focused on supply chain intelligence, including demand forecasting, inventory optimization, distribution order management, and advanced analytics. The team develops data-driven products, algorithms, and automation solutions that are used across HP Indigo’s SPO organization to improve decision-making, operational efficiency, and customer support. Responsibilities: Design, build, and maintain robust data pipelines and ETL processes to support supply chain analytics and planning systems Develop and manage databases, including schema design, query optimization, and ensuring data integrity and availability Build and deploy internal automation tools and data products used across the SPO organization Develop and maintain BI dashboards (Tableau or Power BI) to provide actionable insights to stakeholders Collaborate closely with Data Scientists and Data Analysts to translate business needs into scalable data solutions Maintain and improve server infrastructure hosting scripts, databases, and algorithms Ensure data quality, documentation, and best practices across all data assets Requirements: Education: B.Sc. in Computer Science, Information Systems, Industrial Engineering, or a related field, or equivalent practical experience. Professional experience: At least five years of hands-on experience in data engineering, software development, or a closely related area. Python: Advanced proficiency in Python, with experience writing clean, reliable, and production-grade code for data pipelines, automation, and internal applications. SQL and databases: Strong SQL skills and a solid understanding of database administration concepts, including schema design, indexing, query optimization, performance tuning, and data pipeline architecture. Data engineering: Proven experience designing, building, and maintaining scalable data pipelines and data infrastructure. BI and visualization: Experience developing dashboards and reports using Tableau or Power BI. Analytical mindset: A passion for data analysis, product development, automation, and solving complex business problems. Problem-solving: Strong analytical thinking and structured problem-solving capabilities. Communication: Good verbal and written English communication skills. Collaboration: Strong interpersonal skills and the ability to influence and drive action across multiple stakeholders without direct authority. Advantages: Experience with Windows Server management, maintenance, and optimization. Experience with Databricks. Understanding of supply chain operations and planning processes. Knowledge of machine learning, statistics, and data science concepts. Experience with AI tools, AI-powered applications, agents, or LLM-based solutions. Familiarity with Microsoft 365 tools, particularly Power Apps and Power Automate. Previous experience working in a supply chain, planning, logistics, or operations environment Offer: CIM 24 days of annual leave Meal tickets Private Medical Subscription
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.