📋 Job Details at a Glance 📍 Location Gurugram, Haryana, India 🏢 Company Google 👥 Experience 1-3 years 🎓 Qualification Bachelor’s degree 📅 Eligible Batch 2021, 2022, 2023, 2024, 2025 📄 Job Type Full Time 💰 Salary ₹20–₹35 LPA (estimated) 🏢 Industry Technology 🛠 Key Skills Data engineering database engineering data pipelines data modelling large-scale data processing algorithms software development technical troubleshooting client-facing project management Hadoop Data Engineer at Google — Full Details & How to Apply Google is seeking a Data Engineer in Gurugram, Haryana, India , where you'll contribute to building reliable data infrastructure that supports global operations. This role is pivotal as the demand for data engineers surges, making it an essential position for Google ’s operational success. The importance of the Data Engineer role in the technology sector cannot be overstated. As organizations increasingly depend on data-driven decision-making, skilled professionals are crucial for ensuring data accessibility and reliability. This trend highlights the growing need for data engineering expertise, particularly within a leading company like Google . What sets Google apart as an employer is its commitment to innovation and excellence. Founded in 1998 , Google employs over 156,500 people globally and is known for its groundbreaking products, including Google Search and Google Cloud. This environment fosters a culture of creativity and collaboration, making it an ideal place for aspiring data engineers. We encourage 2021, 2022, 2023, 2024, 2025 graduates with a Bachelor’s degree and 1-3 years experience to apply for this role, which offers a competitive salary of ₹20–₹35 LPA (estimated) . This is a fantastic opportunity for freshers to kickstart their careers in one of the most sought-after fields in technology. As a Data Engineer , you will work with advanced technologies such as Hadoop , Spark , SQL , NoSQL , and Python . This experience not only enhances your technical skills but also opens doors to various career paths in data science and analytics, setting you apart from competitors in the job market. 📊 Role Difficulty: Medium | Competition Level: High | Fresher Friendly: Yes NexisGrow.com features this opportunity as part of its curated tech job listings. All details are sourced from the official job posting. Apply online before the opportunity closes. Job Role & Responsibilities The core mission of the Data Engineer role at Google is to design and build robust data infrastructure that supports data-driven projects, enhancing overall data accessibility and processing efficiency. Design and build reliable data infrastructure using Hadoop and Spark to support various data-driven projects. Develop scalable data pipelines that enhance data processing efficiency and reliability, utilizing SQL and NoSQL databases. Collaborate cross-functionally with product and engineering teams to ensure data alignment with business objectives, focusing on data modelling . Monitor and optimize data models to improve performance metrics and data accessibility, leveraging tools like Hive and MapReduce . Take ownership of troubleshooting complex technical issues, ensuring minimal disruption to data services through effective technical troubleshooting . Document data processes and communicate findings to stakeholders to facilitate informed decision-making, enhancing client-facing project management . Engage with clients to understand their data needs and provide tailored solutions, ensuring alignment with large-scale data processing requirements. At Google , you will take ownership of your projects, directly impacting data services and contributing to the overall success of the organization. Required Skills & Technical Competencies The ideal candidate for the Data Engineer position will possess a strong technical skill profile, essential for building and maintaining efficient data systems. Technical Skills Data engineering — intermediate — essential for building and maintaining data pipelines, requiring proficiency in SQL and NoSQL databases. Database engineering — intermediate — critical for optimizing data storage solutions, particularly with MongoDB in a cloud environment. Large-scale data processing — advanced — utilized daily to handle vast datasets efficiently using tools like MapReduce . Technical troubleshooting — intermediate — necessary for resolving issues swiftly, ensuring data integrity and availability. Proficiency in Python — intermediate — evaluated through coding assessments to ensure candidates can implement algorithms effectively. Proficiency in Java — intermediate — required for developing scalable applications and data processing solutions. When showcasing these technical skills in your resume or interview, emphasize specific projects or experiences that demonstrate your proficiency with the mentioned tools and technologies. Eligibility Criteria This role is designed for recent graduates and early-career professionals eager to develop their expertise in data engineering. A Bachelor’s degree in Computer Science , Engineering , or related fields is required. Eligible batches include 2021 to 2025 , allowing recent graduates to apply. Candidates with 1-3 years of experience are preferred, but freshers with relevant internships or projects are also encouraged. A minimum CGPA of 7.0 is recommended to demonstrate academic competency in technical subjects. Having a portfolio or GitHub showcasing relevant projects can significantly enhance your application. Documentation & Portfolio Requirements Ensure your resume is clear and concise, highlighting relevant experiences and skills. Include links to your portfolio or GitHub to showcase your projects. Pro tip: Tailor your application to highlight specific experiences with Hadoop , Spark , and data pipeline projects to stand out. Salary for Data Engineer at Google 💰 Compensation ₹20–₹35 LPA (estimated) The advertised compensation for the Data Engineer role at Google is ₹20–₹35 LPA (estimated) . The exact in-hand figure and any additional components are confirmed by the company during the offer or HR discussion stage. Recommended Courses & Preparation Tips for Data Engineer Upskilling with the right resources significantly improves your selection odds for the Data Engineer role at Google . Recommended Courses & Resources large-scale data processing — Essential for handling big data efficiently in engineering tasks. SQL — Fundamental for database management and querying data effectively. MongoDB — Important for working with NoSQL databases in data engineering. Java — A key programming language for building data processing applications. KodNest — Provides hands-on experience with data engineering projects. Boost your profile with relevant certifications at NexisGrow GetCertified — strengthen your application before you apply. Common Mistakes to Avoid ❌ Failing to tailor your resume for the specific skills and technologies listed in the job description — Customize your resume to match the job requirements. ❌ Neglecting to showcase relevant internships or projects that demonstrate your data engineering capabilities — Highlight applicable experiences prominently. ❌ Using generic language instead of specific metrics or outcomes achieved in past roles — Use quantifiable achievements to stand out. ❌ Overlooking the importance of clear documentation of your technical skills and experiences — Ensure your skills are well-documented and easy to find. ❌ Not preparing for technical interviews by practicing coding problems relevant to data engineering — Engage in mock interviews and coding challenges. ❌ Ignoring the significance of soft skills, such as communication and teamwork, in your application — Emphasize your collaborative experiences. Before You Apply — Checklist ✅ Research Google’s culture and values to align your application with their expectations. ✅ Update your resume to reflect relevant skills and experiences tailored to the Data Engineer role. ✅ Prepare a cover letter that highlights your interest in data engineering and your fit for the role. ✅ Gather references who can speak to your technical abilities and teamwork skills. ✅ Review your online presence, including LinkedIn and GitHub, to ensure consistency with your application. ✅ Practice common data engineering interview questions and coding challenges. ✅ Double-check application deadlines and ensure all materials are submitted on time. ✅ Follow up on your application status after submission to express continued interest. Resume Tailoring & ATS Keywords for Data Engineer Optimizing your resume for ATS is crucial for securing an interview for the Data Engineer role at Google . ATS Keywords to Include Data engineering Database engineering Data pipelines Data modelling Large-scale data processing Hadoop Spark SQL NoSQL Python Java Technical troubleshooting Resume Tips for This Role Highlight specific projects where you utilized data engineering skills, particularly with tools mentioned in the job description. Emphasize teamwork and collaboration experiences, especially in cross-functional settings. Include links to your portfolio or GitHub to showcase your coding skills and relevant projects. Optimize your resume for ATS by using keywords from the job description to ensure it passes initial screenings. Avoid including unrelated work experiences or skills that do not align with the data engineering role. Build an ATS-optimized resume for this role using NexisGrow Resume Builder — free for all job seekers. Pro tip: Avoid including generic skills that do not directly relate to data engineering, as they dilute your application. How to Apply for Data Engineer at Google Apply Now — Google Visit the Google Careers page and search for the Data Engineer position. Upload your resume, ensuring it highlights relevant skills and experiences. Fill out the application form accurately, providing all requested information. After submission, you can expect a confirmation email regarding your application status. Use the application portal to track the status of your application and any updates. Applications reviewed on a rolling basis — early submission recommended. Apply Now — Google NexisGrow.com does not charge any fees for job applications. Google Google was founded in 1998 and has grown to become a leader in the technology sector, with its headquarters located in Mountain View, California . Today, Google employs over 156,500 employees globally, with a significant presence in Gurugram, Haryana , contributing to its expansive global footprint. The core products of Google include Google Search , YouTube , and Google Cloud , which serve billions of users daily. These platforms are integral to digital experiences, showcasing Google's commitment to innovation and user-centric design in the technology landscape. Google has consistently ranked among the top companies to work for, receiving accolades such as the 2022 Glassdoor Employees' Choice Award . The company is recognized for its innovative culture and comprehensive employee benefits, which include wellness programs and professional development opportunities. Recently, Google announced plans to expand its data centers in India , reflecting its commitment to enhancing Google Cloud services in the region. This initiative is part of a broader strategy to invest over $10 billion in India over the next few years, further solidifying its presence. Starting a career at Google as a Data Engineer offers unparalleled opportunities for professional growth. Freshers can access cutting-edge technologies and work on large-scale data processing projects, positioning themselves for success in the ever-evolving technology sector. Company Details Industry Technology Location Gurugram, Haryana, India Connect With Us Careers Apply Now Website 🔗 google.com Frequently Asked Questions Interview · Role · Salary · Growth ? Who can apply for Data Engineer at Google? Eligibility Tap to expand + Answer Candidates with Bachelor’s degree and 1-3 years experience are eligible. Eligible batches: 2021, 2022, 2023, 2024, 2025. ? What skills are most important for this role? Skills Tap to expand + Answer Key skills: Data engineering, database engineering, data pipelines, data modelling, large-scale data processing. Strong fundamentals and practical project experience matter most. ? What is the salary for this position? Salary Tap to expand + Answer Compensation: ₹20–₹35 LPA (estimated). Final offer depends on skills, experience, and interview performance. ? What is the interview process at Google? Interview Tap to expand + Answer Typically: Resume shortlisting → Online test → Technical interview(s) → HR round. ? Is this role remote, hybrid, or onsite? Work Mode Tap to expand + Answer Work mode varies by team. Confirm with HR during recruitment. ? What is the career growth path from this role? Growth Tap to expand + Answer Structured appraisals every 6–12 months. Senior roles accessible within 12–18 months based on performance. ? How do I apply? Application Tap to expand + Answer Apply via the official link in How to Apply section. Highlight: Data engineering, database engineering, data pipelines, data modelling, large-scale data processing. ? Is there a probation period? Probation Tap to expand + Answer Standard 3–6 months probation. Confirmation follows successful completion. ? How to prepare for the Data Engineer interview? Preparation Tap to expand + Answer (1) Core concepts of Data engineering, database engineering, data pipelines, data modelling, large-scale data processing, (2) 2–3 project walkthroughs, (3) Problem-solving, (4) Google research, (5) Clear communication. ? What is the work culture like at Google? Culture Tap to expand + Answer Research on LinkedIn and Glassdoor for authentic employee reviews. NexisGrow.com features only verified employers. 🔗 Explore More on NexisGrow More jobs in Gurugram Browse all Tech jobs More jobs at Google Work From Home jobs Ready to Apply? Don't Miss This Opportunity! Apply only via the official link. NexisGrow.com charges zero application fees. 👉 Apply Now — Official Link NexisGrow.com does not charge any application or registration fees. Beware of fraudulent offers. Naukri ki baat, NexisGrow ke saath • NexisGrow.com