📋 Job Details at a Glance 📍 Location Pune, India 🏢 Company Mastercard 👥 Experience 1-2 years 🎓 Qualification 1–2 years. Hands-on with Python, Java, SQL, Kafka, Docker, AWS, GCP, Azure, REST APIs, APIs, Git, CI/CD, Spark, Microservices. Relevant technical / engineering background 📅 Eligible Batch 2024, 2025, 2026 📄 Job Type Full Time 💰 Salary Not Disclosed 🏢 Industry Technology 🛠 Key Skills Python Java SQL Kafka Docker AWS GCP Azure Data Engineer II at Mastercard — Full Details & How to Apply Mastercard is seeking a Data Engineer II in Pune, India , responsible for developing and maintaining batch and near real-time data pipelines using Python, Spark, and Kafka . This role offers hands-on experience with core data engineering tools in a technology-driven environment. The Data Engineer II role directly supports data processing solutions by building ETL/ELT pipelines and enabling real-time data ingestion through Kafka and Spark . Candidates will work on scalable data pipelines that process large volumes of transactional and operational data, ensuring data accuracy and availability for analytics and business operations. The position emphasizes practical implementation of data workflows using Python, Java, SQL, Docker, AWS, GCP, Azure , and REST APIs . Mastercard recruitment for this role highlights a focus on technical execution in data engineering. The job is part of Mastercard ’s technology operations in Pune, India, and requires candidates to demonstrate proficiency in Python, Java, SQL, Kafka, Docker, AWS, GCP, Azure, Git, CI/CD, Spark, and Microservices . The role is designed for individuals with a technical engineering background and hands-on experience in data pipeline development. 2024, 2025, 2026 graduates should apply. Candidates must have 1–2 years. Hands-on with Python, Java, SQL, Kafka, Docker, AWS, GCP, Azure, REST APIs, APIs, Git, CI/CD, Spark, Microservices. Relevant technical / engineering background and 1-2 years experience . The salary for this position is Not Disclosed . Applicants will gain practical experience with Python , Java , SQL , Kafka , Docker , AWS , GCP , Azure , Spark , and Microservices . This role provides a foundation for advancing into senior data engineering or data platform roles, with exposure to enterprise-grade data infrastructure and real-time processing systems. 📊 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 designs and maintains scalable data pipelines that process transactional and behavioral data in real time, ensuring data integrity and operational efficiency across global payment systems. This role directly supports real-time fraud detection and customer analytics through reliable, high-throughput data flows. Develop batch and near real-time data pipelines using Python and Java to process structured and semi-structured transaction data from source systems. Build ETL/ELT pipelines with SQL and Java to extract, transform, and load data from relational databases into data lakes for downstream analytics. Collaborate with engineering teams to implement scalable data processing solutions using Spark and Java for high-volume batch jobs. Perform data validation and reconciliation using SQL queries to verify data consistency across source and target systems. Assist in developing real-time data ingestion solutions using Kafka and Spark Structured Streaming to capture event streams from payment gateways. Document data pipeline workflows and performance metrics, including latency , throughput , and error rates , for audit and operational reporting. Troubleshoot data processing failures in Spark and Java jobs, identifying root causes and implementing fixes to reduce downtime. Support CI/CD pipelines by integrating Git and Docker to deploy and test data processing scripts in staging environments. This role requires direct ownership of data pipeline performance, where every data validation step , error log , and pipeline runtime metric contributes to system reliability and business decision accuracy. Required Skills & Technical Competencies The Data Engineer II role demands a strong foundation in core programming and data processing tools, with emphasis on Python , Java , SQL , Kafka , and Spark for building production-grade data systems. Candidates must demonstrate hands-on experience with these technologies in real-world data workflows. Technical Skills Python — essential — used for developing data pipelines, performing data manipulation, and implementing ETL logic in Spark and SQL environments. Java — intermediate — used in building batch processing solutions and ETL pipelines, particularly in Spark and Java-based data processing frameworks. SQL — critical — used for querying structured data, validating data integrity, and managing metadata within data pipelines. Kafka — essential — used for real-time data ingestion, handling high-volume event streams from payment systems, and integrating with Spark Structured Streaming . Docker — intermediate — used to containerize data processing scripts and deploy them in isolated, reproducible environments across AWS and GCP . AWS — intermediate — used to deploy and manage data pipelines, storage, and compute resources on Amazon S3, EC2, and EMR platforms. GCP — intermediate — used for hosting data lakes, running Spark jobs, and managing cloud-based data processing workloads. Azure — intermediate — used for deploying and monitoring data pipelines in cloud environments with Azure Data Factory and Blob Storage. When showcasing these skills, emphasize specific projects where you used Python to build a Spark pipeline, SQL to validate data quality, or Kafka to ingest real-time transaction events with measurable latency and throughput metrics. Eligibility Criteria This role is designed for candidates with a technical engineering background , 1–2 years of hands-on experience, and a demonstrated ability to work with data pipelines and cloud platforms in real-world environments. Must hold a Bachelor’s degree in Computer Science, Engineering, or a related technical field. Eligible for 2024 , 2025 , and 2026 intake batches only. Minimum of 1 year of hands-on experience with Python , SQL , or Java in data processing or backend systems. CGPA of 3.0 or above is required for admission consideration. Must have a portfolio demonstrating at least two working data pipeline projects using Spark , Kafka , or SQL . Experience with CI/CD workflows using Git and Docker is preferred but not mandatory. Documentation & Portfolio Requirements Your resume must include a clear section detailing your technical projects , with specific tools used (e.g., Python , Spark ) and measurable outcomes (e.g., data throughput , latency reduction). Include links to GitHub repositories or live demos where applicable. For this role, prioritize projects that involve real-time data ingestion using Kafka and Spark Structured Streaming , or batch ETL pipelines with SQL and Java . Highlight metrics like error rate , processing time , and data volume to show technical depth and operational impact. 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 the Data Engineer II 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. Docker — Useful for containerizing applications and ensuring consistency across environments. 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 ❌ Applying without demonstrating experience with Python or Java — Include specific projects or tasks. ❌ Using a generic resume — Tailor it to match the responsibilities outlined in the job description. ❌ Listing technologies like AWS or Docker without context — Provide details on how they were applied in previous roles. ❌ Ignoring the specific experience requirement of 1-2 years — Ensure you meet the relevant background. ❌ Adding unrelated technologies or unsupported claims — Focus on substantiated experience only. ❌ Not verifying the official Apply URL — Always check the job details before submission. 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 the Data Engineer II role to ensure it passes initial screenings and highlights your relevant skills. ATS Keywords to Include Python Java SQL Kafka Docker AWS GCP Azure Spark Microservices REST APIs Git Resume Tips for This Role Highlight your experience with Python and Java prominently on your resume. Emphasize hands-on experience with technologies like Kafka and Spark . Showcase a project involving building data pipelines or working with ETL processes. Use exact keywords from the job description naturally to align with ATS requirements. Avoid adding unsupported claims or technologies that cannot be substantiated with experience. Build an ATS-optimized resume for this role using NexisGrow Resume Builder — free for all job seekers. Pro tip: Avoid including 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 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 payment systems sector. This Data Engineer II role is onsite and focuses on building scalable data processing solutions within a technology-driven environment. The team develops batch and near real-time data pipelines using Python , Java , SQL , Kafka , and Spark. They build ETL/ELT pipelines and support real-time data ingestion through streaming technologies like Kafka and Spark Structured Streaming. This role contributes to Mastercard ’s data engineering efforts in payment systems, enabling efficient data processing and real-time insights. Early-career professionals gain hands-on exposure to core tools such as Python , Java , SQL , Kafka , Docker , AWS , GCP , Azure , and Spark—key technologies in modern data engineering workflows. 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 background and 1-2 years of experience, from the eligible batches of 2024, 2025, and 2026. ? What technical skills are most important for this role? Skills Tap to expand + Answer Python, Java, SQL, Kafka, Docker, AWS, GCP, Azure, Spark, and Microservices are crucial for this position. ? What is the expected salary for this position? Salary Tap to expand + Answer Salary Display is Not Disclosed, which is the only salary information available. ? 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 Review the job description, practice coding in Python and Java, familiarize yourself with Kafka and Spark, prepare to discuss data pipeline projects, and understand ETL processes. ? Is this role remote, hybrid, or onsite? Work Mode Tap to expand + Answer This role is onsite, as specified in the job posting. ? What career exposure can this role provide? Growth Tap to expand + Answer This role offers exposure to data engineering practices, real-time data processing, and collaboration with engineering teams. ? What should I highlight in my resume for this role? Resume Tap to expand + Answer Highlight skills in Python, Java, SQL, experience with data pipelines, and any relevant projects or internships. ? 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 engineering teams and stakeholders, working onsite. ? Can freshers apply for this role? Fresher Tap to expand + Answer No, the role requires 1-2 years of experience. 🔗 Explore More on NexisGrow More jobs in Pune Browse all Tech jobs Latest Fresher jobs More jobs at Mastercard Work From Home jobs Ready to Apply? 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