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Accenture Technology powers our clients to achieve high performance. We combine business and industry insights with innovative technology to drive growth for your business. We extend our technology and business capabilities through a powerful alliance ecosystem of market leaders and innovators to provide our clients the best specialized skills and tailored solutions. We are seeking a highly qualified professional to join our team as an AI Data Engineer (with Google Cloud Platform) . As an essential part of our team, you will be responsible for designing, building, and optimizing scalable data solutions that support analytics, reporting, and AI-driven use cases. We are looking for a professional with strong expertise in GCP, data engineering, and modern data architectures. Qualifications Strong hands-on experience with SQL and Python Deep knowledge of Google Cloud Platform (GCP), with BigQuery expertise being mandatory Minimum knowledge of Generative AI concepts (must have), including embeddings, RAG pipelines, Vertex AI SDK, prompt engineering, and function calling fundamentals Proven track record delivering end-to-end data engineering projects Strong experience in data modeling, data quality, and data governance best practices Experience designing and implementing scalable data pipelines and data platforms Strong understanding of ETL/ELT frameworks and modern data architectures Client-facing experience with the ability to communicate technical concepts to non-technical stakeholders Strong analytical and problem-solving skills Excellent communication and stakeholder management abilities Fluent in English (C1 or above) Responsibilities Design, develop, and maintain scalable data pipelines and data platforms on GCP Build and optimize solutions using BigQuery and other Google Cloud data services Develop and maintain data models that support business reporting, analytics, and operational processes Ensure data quality, governance, security, and compliance standards are consistently applied Collaborate with business and technical stakeholders to gather requirements and translate them into data solutions Monitor and optimize data platform performance, reliability, and cost efficiency Support the implementation of data engineering best practices across projects Contribute to architecture decisions and provide technical guidance to project teams Present technical recommendations and solutions to client stakeholders Support AI and advanced analytics initiatives by preparing and managing high-quality datasets Nice to Have Google Cloud Certifications such as Professional Data Engineer, Professional Cloud Architect, or equivalent Experience with Azure or AWS is considered a plus Additional Information Location: Lisbon, Coimbra or Braga
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.