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We are a consulting company with a bunch of tech-savvy and happy people! We love technology, we love design, and we love quality. Our diversity makes us unique and creates an inclusive and welcoming workplace where every individual is highly valued. With us, everyone can be themselves while respecting others for who they are. We believe that when an amazing mix of people come together and share their knowledge, experiences, and ideas, we can help our clients on a completely different level. We are looking for someone who can start immediately and wants to grow with us! With us, you have great opportunities to make real progress in your career and the chance to take on significant responsibility. About the Role We are looking for a skilled Data Engineer with strong experience in Google Cloud Platform (GCP) , BigQuery , and Big data to design and maintain scalable data pipelines and analytics infrastructure. You will play a key role in building reliable data systems that support reporting, analytics, and advanced data use cases. Experience with Apache Pinot for real-time analytics is a strong plus. Key Responsibilities Design, build, and maintain scalable data pipelines on GCP Develop and optimize data models using dbt Build and manage data warehouses in BigQuery Implement ELT/ETL processes for structured and semi-structured data Ensure data quality, reliability, and performance optimization Optimize query performance and cost efficiency in BigQuery Implement monitoring and validation frameworks for data pipelines Support real-time analytics use cases (Pinot experience is a plus) Maintain documentation and data governance best practices Required Skills & Qualifications 7+ years of experience in Data Engineering Strong hands-on experience with Google Cloud Platform (GCP) Expertise in BigQuery and Big Data concepts. Good understanding of dbt Strong SQL skills (complex transformations and optimization) Experience designing scalable data models Experience building and maintaining ETL/ELT pipelines Understanding of data warehousing concepts Experience with version control (Git) Strong understanding of data performance tuning and cost optimization. Nice to Have Experience with Apache Pinot (real-time OLAP systems) Experience with streaming pipelines (Pub/Sub, Kafka, etc.) Knowledge of data governance and security best practices Experience in high-volume production environments Soft Skills Strong analytical thinking Attention to detail Ownership mindset Ability to work cross-functionally Strong communication skills .
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.