📋 Job Details at a Glance 📍 Location Pune, India 🏢 Company Mastercard 👥 Experience 1-3 years 🎓 Qualification Senior level. Hands-on with Python, Java, SQL, Kafka, AWS, GCP, Azure, APIs, Git, CI/CD, Spark, Microservices. Relevant technical qualification and demonstrated shipping experience 📅 Eligible Batch 2022, 2023, 2024, 2025 📄 Job Type Full Time 💰 Salary Not Disclosed 🏢 Industry Technology 🛠 Key Skills Python Java SQL Kafka AWS GCP Azure APIs Data Engineer II at Mastercard — Full Details & How to Apply Mastercard is hiring a Data Engineer II in Pune, India with hands-on experience in Python, Java, SQL, Kafka, and cloud platforms —a key requirement for building scalable data pipelines in real-world environments. This role is part of Mastercard ’s technology-driven data infrastructure, where engineers directly support data accessibility and usability through pipeline development. The Data Engineer II role focuses on building and maintaining data pipelines that power Mastercard ’s global data ecosystem. These pipelines are essential for processing large-scale transactional and behavioral data, ensuring reliable data flow across systems. The responsibilities involve using tools like Python, Java, SQL, Kafka, Spark, APIs, Git, CI/CD, and microservices , with direct exposure to AWS, GCP, and Azure environments. This work ensures data is accessible, consistent, and ready for downstream analytics and decision-making. Mastercard recruitment for this position emphasizes technical depth and real-world implementation. The role is part of a data engineering team that develops and maintains core data platforms. The job posting specifies that candidates must have senior-level hands-on experience with key technologies and a demonstrated history of shipping data solutions. This reflects a focus on practical, production-grade engineering skills within a technology company. 2022, 2023, 2024, 2025 graduates should apply if they hold a senior level. Hands-on with Python, Java, SQL, Kafka, AWS, GCP, Azure, APIs, Git, CI/CD, Spark, Microservices. Relevant technical qualification and demonstrated shipping experience and have 1-3 years of experience . The salary for this position is Not Disclosed . Applicants will gain hands-on experience with Python, Java, SQL, Kafka, AWS, GCP, Azure, APIs, Git, CI/CD, Spark, and microservices . This role provides a foundation for advancing into senior data engineering or data platform roles, with exposure to enterprise-grade cloud environments and real-time data processing. It supports progression into roles that manage large-scale data systems within financial technology ecosystems. 📊 Role Difficulty: Medium | Competition Level: Medium | Fresher Friendly: No 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. Explore more Data Engineer II jobs , Mastercard recruitment , and Pune, India jobs on our platform. Job Role & Responsibilities The Data Engineer II at Mastercard ensures data pipelines operate with high throughput and zero data loss by building scalable solutions using Apache Spark and SQL . This role directly supports real-time transaction processing and data integrity across global payment systems. Build end-to-end data pipelines using Apache Spark and SQL to process terabytes of transaction data daily with 99.99% accuracy . Maintain existing data pipelines on AWS and Google Cloud Platform to ensure uptime of 99.9% and low-latency response during peak loads. Implement data validation rules using SQL and Kafka to detect anomalies in real-time streaming data with 100% coverage . Develop ETL workflows using Python scripts to extract, transform, and load structured financial data from APIs into cloud databases . Deploy microservices on Azure and AWS using CI/CD pipelines to enable automated deployment of data processing jobs . Collaborate with senior engineers to debug data flow issues in Java-based data services and Kafka clusters during production incidents . Document data modeling decisions and pipeline improvements in Git repositories to ensure traceability and knowledge transfer . Resolve production errors in Spark jobs and cloud storage systems to prevent data corruption and service downtime . This role demands direct ownership of data pipeline performance , with measurable impact on transaction accuracy and system reliability across Mastercard’s global operations . Required Skills & Technical Competencies The Data Engineer II must demonstrate hands-on proficiency in Python , Java , SQL , and cloud platforms to build and maintain production-grade data solutions with high reliability and scalability . Technical Skills Python — intermediate — used for scripting data transformations and automating ETL workflows in Spark and cloud environments . Java — intermediate — used to develop data services and microservices that interface with data pipelines and Kafka . SQL — advanced — essential for querying large datasets , data validation , and schema design in production databases . Kafka — intermediate — used to ingest real-time transaction streams and ensure message durability in high-volume systems . AWS — intermediate — used to deploy and manage data lakes , EMR clusters , and data processing jobs on Amazon S3 and Redshift . GCP — intermediate — used to run Spark on Vertex and manage cloud storage for data ingestion and processing . Azure — intermediate — used to host data microservices and CI/CD pipelines for data engineering workflows . APIs — intermediate — used to consume external financial data and integrate with third-party services via REST and JSON endpoints. When preparing your resume, emphasize specific projects where you used Python or SQL to process real-world data , and highlight deployment on AWS or GCP with measurable outcomes . Eligibility Criteria This role is designed for graduates with a technical degree and 1–3 years of hands-on experience in data engineering or related domains , particularly in cloud-based data processing . Must hold a Bachelor’s degree in Computer Science , Electrical Engineering , or a related technical field . Eligible only for 2022, 2023, 2024, and 2025 batches, with no exceptions for earlier or later years. Must have 1–3 years of hands-on experience in data pipelines or cloud-based data processing projects. Academic performance is not specified, but strong foundational knowledge in data structures and algorithms is expected. Must have a portfolio showcasing Python scripts , SQL queries , or data pipeline designs built with Spark or Kafka . Must have contributed to open-source projects or GitHub repositories involving data engineering tasks. Documentation & Portfolio Requirements Your resume must include a clear section on technical projects with specific tools like Python , SQL , or Spark , and must list GitHub links to working code or pipeline implementations . For this role, prioritize showcasing a real-world data pipeline built with Python and Spark that processes structured or streaming data and includes data validation and error logging — not just theory or small scripts. Salary for Data Engineer II at Mastercard 💰 Compensation Not Disclosed The advertised compensation for the Data Engineer II role at Mastercard is Not Disclosed . 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 II Upskilling with the right resources significantly enhances your chances of selection for this specific role by aligning your skills with the job requirements. Recommended Courses & Resources Python — Essential for data manipulation and analysis in engineering tasks. Java — Important for building scalable data processing applications. SQL — Crucial for database management and querying data efficiently. AWS — Key for cloud-based data solutions and infrastructure management. KodNest — Provides hands-on coding practice relevant to data engineering. Boost your profile with relevant certifications at NexisGrow GetCertified — strengthen your application before you apply. Common Mistakes to Avoid ❌ Applying without demonstrating experience in Python or Java — Ensure these are highlighted. ❌ Using a generic resume — Tailor it to the specific responsibilities and skills listed in the job description. ❌ Listing technologies like AWS or Kafka without detailing their application — Provide context on their use in past projects. ❌ Ignoring the experience requirement of 1-3 years — Ensure you meet this criterion to avoid disqualification. ❌ Adding unrelated technologies or unsupported claims — Focus on relevant skills to avoid ATS penalties. ❌ Failing to verify the official Apply URL — Always check the link before submitting your application. Before You Apply — Checklist ✅ Confirm the job title, company, location, work mode, and experience requirement. ✅ Check that you meet the supplied qualification criteria. ✅ Verify eligibility against the supplied eligible batches and experience requirement. ✅ Add relevant supplied JD keywords naturally to your resume. ✅ Highlight projects or experience related to the supplied technologies and responsibilities. ✅ Remove unsupported technologies, achievements, or experience claims. ✅ Open and verify the supplied Apply URL before submitting the application. ✅ Save the job details, application date, and role-specific resume version for tracking. Resume Tailoring & ATS Keywords for Data Engineer II Optimizing your resume for ATS is crucial for standing out in the application process for this role. ATS Keywords to Include Python Java SQL Kafka AWS GCP Azure APIs Git CI/CD Spark Microservices Resume Tips for This Role Highlight your proficiency in Python , as it is a critical skill for the role. Emphasize experience with cloud technologies like AWS and GCP , as they are essential for the job. Showcase a project that involved building data pipelines or using Spark . Use exact keywords from the job description naturally to align with ATS requirements. Avoid including unsupported claims or technologies that you cannot substantiate. Build an ATS-optimized resume for this role using NexisGrow Resume Builder — free for all job seekers. Pro Tip: Do not include unrelated technologies or unsupported claims in your resume for this role. How to Apply for Data Engineer II at Mastercard Apply Now — Mastercard Open the official apply URL and confirm the job title and company is correctly displayed. Prepare a resume that aligns with the required skills, responsibilities, qualifications, and experience for the Data Engineer II role. Complete the official application form accurately, ensuring all information is truthful and avoiding unsupported claims. Submit the application and save the confirmation or application reference number if provided by the portal. Record the application date and monitor the company’s official job portal or your registered email for updates. Applications are reviewed on a rolling basis — early submission is recommended. Apply Now — Mastercard NexisGrow.com does not charge any fees for job applications. Mastercard Mastercard is a technology company based in Pune, India, operating in the technology sector. This Data Engineer II role is onsite and focuses on building scalable data platforms within Mastercard ’s global data ecosystem. The team develops and maintains data pipelines using Python , Java , SQL , Kafka , and cloud platforms like AWS , GCP , and Azure . Responsibilities include ETL/ELT pipelines, data validation, quality checks, and API integrations. This role supports high-impact projects through collaboration with senior engineers, contributing to core data solutions. Early-career engineers gain hands-on exposure to cloud technologies, data engineering practices, and real-world data pipeline development using tools like Kafka , Spark, and CI/CD systems. Company Details Industry Technology Location Pune, India Connect With Us Careers Apply Now Website 🔗 mastercard.wd1.myworkdayjobs.com Frequently Asked Questions Interview · Role · Salary · Growth ? Who can apply for this role? Eligibility Tap to expand + Answer Candidates with a relevant technical qualification and 1-3 years of experience from the eligible batches of 2022, 2023, 2024, and 2025 can apply. ? What technical skills are most important for this role? Skills Tap to expand + Answer Key skills include Python, Java, SQL, Kafka, AWS, GCP, and Azure. ? What is the expected salary for this position? Salary Tap to expand + Answer Salary Display is 'Not Disclosed'. ? What should I expect after applying? Hiring Process Tap to expand + Answer The exact hiring stages are not specified in the job posting. ? How should I prepare for the interview? Preparation Tap to expand + Answer 1. Review data engineering concepts. 2. Practice coding in Python and Java. 3. Familiarize yourself with AWS, GCP, and Azure. 4. Prepare examples of past projects. 5. Understand data pipeline architecture. ? Is this role remote, hybrid, or onsite? Work Mode Tap to expand + Answer This role is onsite in Pune, India. ? What career exposure can this role provide? Growth Tap to expand + Answer The role provides exposure to cloud technologies, data engineering practices, and collaboration with senior engineers. ? What should I highlight in my resume for this role? Resume Tap to expand + Answer Highlight skills in Python, Java, SQL, and experience with data pipelines and cloud technologies. ? Is there a last date to apply? Application Tap to expand + Answer Not specified in the job posting. ? Is there a probation period? Probation Tap to expand + Answer Not specified in the job posting. ? What is the work environment like for this role? Culture Tap to expand + Answer The role involves collaboration with senior engineers in developing data solutions. ? Can freshers apply for this role? Fresher Tap to expand + Answer No, as the experience requirement is 1-3 years. 🔗 Explore More on NexisGrow More jobs in Pune Browse all Tech jobs More jobs at Mastercard 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. 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