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About the Role We are seeking a highly motivated and hands-on GCP Data Engineer to support the development and delivery of modern enterprise data and AI platforms on Google Cloud Platform (GCP). This role will work closely with Lead Data Engineers, Enterprise Architects, analytics teams, and AI/ML teams to build scalable, reliable, and AI-ready data pipelines and cloud-native data solutions that support enterprise analytics, intelligent automation, and digital transformation initiatives. The ideal candidate should possess strong foundations in cloud data engineering, distributed data processing, and modern data platform development, along with a passion for building high-quality, scalable, and reusable data solutions in a fast-paced enterprise environment. This role offers an excellent opportunity to work on large-scale data modernization, semantic data enablement, and next-generation AI data ecosystems. Job Location : Bangalore, Pune, Mumbai work Timings : 01.00 P.M. - 10.00 P.M. Notice Period : Immediate to 15 Days (Preferred) Technical Expertise Required Area Skills / Technologies Cloud Data Engineering GCP, BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage Data Processing SQL, Python, PySpark, DBT Streaming & Pipelines Apache Beam, batch & real-time processing Workflow Orchestration Cloud Composer (Airflow), Workflows Semantic & Analytics Basic semantic modeling concepts, reporting datasets, Looker exposure preferred AI/ML Enablement Vertex AI exposure, BigQuery ML, GenAI ecosystem awareness Metadata & Governance Data Catalog, metadata management, lineage concepts DevOps & Automation CI/CD concepts, Git, automation frameworks Qualifications Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.36 years of experience in data engineering and cloud-based data platform development.Hands-on experience working with Google Cloud Platform (GCP) data services.Strong SQL and Python programming skills.Experience developing scalable ETL/ELT pipelines and distributed data processing workflows.Understanding of modern data architecture concepts including data lakes, data warehouses, and streaming pipelines.Exposure to analytics, AI/ML, or GenAI-enabled data ecosystems preferred.Strong analytical, troubleshooting, and problem-solving skills.Ability to work collaboratively in Agile and cross-functional delivery teams.GCP certifications such as Associate Cloud Engineer or Professional Data Engineer are a plus. Preferred Experience Exposure to enterprise-scale data modernization initiatives. Familiarity with modern data engineering and data product development practices. Experience working with semantic layers, reporting platforms, or BI ecosystems. Exposure to AI-ready data platforms and modern analytics ecosystems. Experience in retail, marketing, customer analytics, or digital commerce domains is an advantage. Data delivery, re-designing infrastructure for greater scalability, etc Builds analytics tools that utilise the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics Works with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs Keeps our data separated and secure Creates data tools for analytics and data scientist team members that assist them in building and optimising our product into an innovative industry leader Works with data and analytics experts to strive for greater functionality in our data systems .
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.