📋 Job Details at a Glance 📍 Location Pune, India 🏢 Company Mastercard 👥 Experience 1-3 years 🎓 Qualification Hands-on with Python, JavaScript, SQL, Kafka, AWS, Spark. Relevant technical qualification and demonstrated shipping experience 📅 Eligible Batch 2023, 2024, 2025, 2026 📄 Job Type Full Time 💰 Salary Not Disclosed 🏢 Industry Technology 🛠 Key Skills Python JavaScript SQL Kafka AWS Spark Databricks Cloudera Data Engineer II at Mastercard — Full Details & How to Apply Mastercard is hiring a Data Engineer II in Pune, India to automate data ETL processes for Data Analysts and Data Scientists. This role requires hands-on experience with Python, SQL, Spark, and AWS , and candidates must demonstrate shipping experience with real-world data pipelines. This Data Engineer II role supports data-driven decision-making by building and maintaining database technologies. The position directly involves managing large-scale data using SQL and Spark to process data in cloud environments. Automation of ETL workflows ensures consistent data flow, improving operational efficiency for data teams. The role relies on proven technical skills in Kafka and Databricks to handle real-time and batch data processing. The job posting identifies Mastercard as a technology company with a need for skilled data engineers in Pune, India . The role is part of a team focused on data operations, where technical qualifications and demonstrated shipping experience are essential. The position emphasizes hands-on work with cloud platforms and data engineering tools. 2023, 2024, 2025, 2026 graduates are eligible. Candidates must have hands-on with Python, JavaScript, SQL, Kafka, AWS, Spark and possess relevant technical qualification and demonstrated shipping experience . The role requires 1-3 years of experience . Salary is not disclosed . Applicants will gain hands-on experience with Python , JavaScript , SQL , Kafka , AWS , Spark , Databricks , and Cloudera . This role builds foundational skills in data engineering and database administration, offering a clear path toward advanced data roles in technology and finance. It provides exposure to enterprise-grade data infrastructure and cloud-based data workflows. 📊 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 reliable, scalable data pipelines by building and maintaining database technologies using SQL , Spark , and Kafka to support real-time transaction processing and analytics. This role directly impacts data accuracy, latency, and system performance across global payment operations. Build scalable data pipelines using Spark to process large-scale transaction datasets from AWS S3 buckets and deliver them to Databricks for downstream analysis. Automate ETL workflows with Python scripts that execute SQL queries on daily batch jobs, reducing manual intervention by 70% and improving data consistency. Collaborate with Data Analysts and Data Scientists to define data requirements and validate SQL queries for reporting and model training using Cloudera data platforms. Monitor data quality using Spark job metrics such as job duration, error rate, and data volume per batch, ensuring data completeness exceeds 99.9%. Support legacy database systems by maintaining SQL stored procedures and Python scripts that interface with Amazon RDS and Kafka streams. Document data processing workflows in Confluence or GitHub with versioned SQL scripts and Python code, enabling audit trails and onboarding for new engineers. Perform root cause analysis on data failures using Kafka consumer logs and Spark job logs to identify message drops or processing errors. Optimize data pipeline performance by tuning Spark configurations such as executor memory and parallelism, reducing job runtime by at least 20%. This role demands full ownership of data pipeline reliability, where every metric , tool , and automation decision directly affects data accuracy and system uptime in high-volume financial operations. Required Skills & Technical Competencies The Data Engineer II role requires a strong foundation in Python , SQL , Spark , Databricks , and Cloudera to execute data engineering tasks at scale. These skills are essential for building, maintaining, and monitoring production-grade data systems. Technical Skills Python — intermediate — used for scripting ETL processes, automating SQL execution, and handling data validation in Spark jobs. JavaScript — entry — used for lightweight data validation and integration with web-based data ingestion tools, though not central to core data processing. SQL — advanced — used to write complex queries for large datasets, manage database schemas , and validate data integrity in Amazon RDS and Cloudera environments. Kafka — intermediate — used to ingest real-time transaction data streams and manage message consumption via Spark consumers in AWS environments. AWS — intermediate — used to deploy and manage data storage in S3 and Redshift , and to configure Spark jobs on EC2 instances. Spark — advanced — used to process petabyte-scale data, execute ETL workflows, and optimize job performance using Spark SQL and Spark Streaming . Databricks — intermediate — used to run Spark jobs, manage notebooks, and deploy data pipelines for analytics teams using SQL and Python . Cloudera — intermediate — used to manage enterprise data platforms, deploy Spark clusters, and maintain SQL data warehouse schemas. When preparing your resume, emphasize specific projects where you used Python and Spark to automate data workflows, and include metrics such as data volume processed or job runtime reduction. Eligibility Criteria This role is designed for candidates with a technical qualification in computer science, data engineering, or a related field and at least 1–3 years of hands-on experience in data engineering using Python , SQL , and Spark . It is not intended for entry-level candidates without demonstrated shipping experience. Must hold a degree in Computer Science, Data Science, or a related technical discipline. Eligible batches are 2023 , 2024 , 2025 , and 2026 . Must have at least 1 year of hands-on experience with Python , SQL , and Spark in real-world data engineering projects. Experience with GitHub repositories or project documentation is required to demonstrate shipping capability. CGPA or academic performance is not specified, but technical competence is mandatory. Must have a portfolio showcasing Python scripts, SQL queries, and Spark ETL workflows with measurable outcomes. Documentation & Portfolio Requirements Your resume must include a clear section on technical projects with GitHub links, showing Python and SQL scripts, Spark job configurations, and data quality metrics such as error rates or processing times. For this role, prioritize showcasing a real-world project where you used Spark to process large datasets and Python to automate data validation — include metrics like data volume, error rate, or runtime reduction to prove 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 being selected for the Data Engineer II role at Mastercard . Recommended Courses & Resources Python — Essential for data manipulation and analysis in engineering tasks. JavaScript — Useful for data visualization and web-based applications. SQL — Critical for database management and querying data efficiently. AWS — Important for cloud-based data storage and processing solutions. 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 — Ensure to include relevant projects. ❌ Using a generic resume — Tailor it to the specific responsibilities listed in the job description. ❌ Listing technologies like Spark without context — Provide details on how they were applied in previous roles. ❌ Ignoring the experience requirement of 1-3 years — This may lead to disqualification. ❌ Adding unrelated technologies or unsupported claims — This may backfire in ATS screening. ❌ Failing to verify the official Apply URL — This could lead to application errors. Before You Apply — Checklist ✅ Confirm the job title, company, location, work mode, and experience requirement. ✅ Check that the candidate meets the supplied qualification criteria. ✅ Verify eligibility against the supplied eligible batches and experience requirement. ✅ Add relevant supplied JD keywords naturally to the 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 the Data Engineer II role at Mastercard . ATS Keywords to Include Python SQL Spark Kafka AWS Databricks Cloudera ETL Data Engineering Database Administration Data Analysis Data Quality Resume Tips for This Role Highlight your experience with Python , as it is a key requirement for the role. Emphasize familiarity with SQL and Spark , showcasing any relevant projects or coursework. Detail a project where you automated ETL processes using the listed technologies. Use exact keywords from the job description to enhance ATS alignment without keyword stuffing. Avoid including unsupported claims about technologies or experiences that cannot be substantiated. Build an ATS-optimized resume for this role using NexisGrow Resume Builder — free for all job seekers. Pro Tip: Avoid including unrelated experiences 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 official company 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 data solutions space. This Data Engineer II role is onsite and supports data teams through database technologies and ETL automation. The team builds and maintains data pipelines using Python , SQL , Kafka , AWS , Spark , and Databricks . They collaborate with Data Analysts and Data Scientists to manage large-scale data and ensure reliable data flow. This role provides early-career exposure to core data engineering tools and responsibilities, including data modeling, ETL processes, and cloud-based data platforms. 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 2023, 2024, 2025, and 2026 batches can apply. ? What technical skills are most important for this role? Skills Tap to expand + Answer The most important skills include Python, SQL, Spark, Kafka, and AWS. ? 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 1. Review SQL and Spark fundamentals. 2. Prepare examples of ETL processes you've automated. 3. Familiarize yourself with cloud platforms like AWS. 4. Understand data quality metrics. 5. Be ready to discuss collaboration experiences. ? 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 offers exposure to data engineering tools and practices, enhancing skills in database technologies and ETL processes. ? What should I highlight in my resume for this role? Resume Tap to expand + Answer Highlight skills in Python, SQL, Spark, and any relevant experience in data engineering or ETL processes. ? 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 Data Analysts and Data Scientists, focusing on data management. ? Can freshers apply for this role? Fresher Tap to expand + Answer No, the experience requirement is 1-3 years, which does not explicitly accept freshers. 🔗 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? 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