{"id":2991276,"url":"https://alion.io/job/mastercard-data-engineer-ii-6","title":"Data Engineer II","company":{"id":252,"name":"Mastercard","domain":"mastercard.com","url":"https://alion.io/company/mastercard","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":87,"open_postings":185,"ghost_share":0.027,"stale_share":0.4,"repost_share":0.092,"time_to_fill_p50_days":26,"computed_at":"2026-10-24T06:02:35Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":15000,"max_usd":39000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":21},"experience_years_min":1,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Java","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Amazon S3","optional":true},{"name":"Databricks","optional":true},{"name":"Docker","optional":true},{"name":"Git","optional":true},{"name":"GitHub Actions","optional":true},{"name":"Jenkins","optional":true},{"name":"NumPy","optional":true},{"name":"Pandas","optional":true},{"name":"Rest API","optional":true}],"status":"live","first_seen_at":"2026-10-21T10:04:31Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-10-24T09:09:51Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Our Purpose\nMastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.\nTitle and Summary\nData Engineer IIJob TitleData Engineer II\nOverview\nWho is Mastercard?\nMastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships, and passion, our innovations help individuals, financial institutions, governments, and businesses realize their greatest potential.\nThe Mastercard Services organization is a key differentiator, delivering cutting-edge solutions used by some of the world’s largest organizations to make critical business decisions. Focused on innovation and scale, Services provides data-driven capabilities across consulting, analytics, experimentation, and risk management.\nTeam Overview\nAs part of Mastercard’s Data Platform & Orchestration team, you will contribute to building next-generation data platforms that are critical to our global data ecosystem.\nOur team develops and operates scalable platform capabilities, including:\nCloud-native infrastructure and application provisioning\nStandardized CI/CD pipelines and engineering tooling\nReusable frameworks and data platform components\nThese platforms enable teams to build, deploy, and operate data-driven solutions efficiently and securely at scale.\nRole Overview\nData Platform & Orchestration is seeking a Data Engineer I to contribute to the development of cloud-native data platforms supporting Mastercard's global data ecosystem.\nThis role is ideal for an early-career engineer who is passionate about data engineering, distributed systems, and cloud technologies. You will work closely with senior engineers to build, test, deploy, and support scalable data solutions that power critical business capabilities.\nYou will gain hands-on experience with modern data engineering technologies including Spark, Kafka, cloud platforms, and data processing frameworks while contributing to high-impact projects across Mastercard's data landscape.\nKey Responsibilities\nDevelop and maintain batch and near real-time data pipelines using Java, Python, Spark, and SQL\nBuild and support ETL/ELT pipelines for processing structured and semi-structured data\nContribute to the development of scalable data processing solutions across Data Lake and Data Warehouse environments\nAssist in developing real-time data ingestion and streaming solutions using Kafka and Spark Structured Streaming\nPerform data validation, reconciliation, and quality checks to ensure reliable data delivery\nCollaborate with senior engineers to troubleshoot and resolve data pipeline and production issues\nWrite efficient SQL queries and optimize data processing jobs for performance and scalability\nDevelop and deploy applications and data pipelines in cloud environments such as AWS, Azure, or GCP\nContribute to automation, monitoring, and observability initiatives to improve platform reliability\nSupport CI/CD activities including code integration, testing, deployment, and release processes\nParticipate in code reviews and follow engineering best practices for secure and maintainable software development\nBuild reusable components and utilities that improve team productivity and consistency\nCollaborate effectively with product owners, architects, data engineers, and platform teams\nSupport AI and machine learning initiatives by developing, validating, and preparing data pipelines used for analytics, predictive modeling, and Generative AI applications\nExplore modern AI-enabled data engineering capabilities, including metadata-driven pipelines, data quality automation, and intelligent operational monitoring\nContinuously learn and adopt new technologies, tools, and engineering practice\nRequired Skills & Qualifications\n1-2 years of experience in software engineering, data engineering, or related technical roles\nKnowledge of Java (JDK 8+) or Python programming, Good to have AI exposure\nUnderstanding of object-oriented programming concepts and software development fundamentals\nFamiliarity with REST APIs and microservices concepts\nBasic hands-on experience with Apache Spark, SQL, and data processing concepts\nUnderstanding of ETL/ELT workflows and data pipeline architectures\nKnowledge of relational databases and data modeling fundamentals\nBasic understanding of Kafka or other messaging platforms\nFamiliarity with distributed systems concepts and data processing at scale\nExperience or academic exposure to AWS, Azure, or GCP\nFamiliarity with cloud storage and compute services such as S3, ADLS, Databricks, or similar platforms\nBasic understanding of containerization technologies such as Docker\nFamiliarity using Git for source code management, CI/CD tools such as Jenkins, GitHub Actions, or similar platforms\nUnderstanding of software testing concepts and unit testing frameworks\nExposure to monitoring and logging tools is a plus\nBasic understanding of AI/ML concepts and how data engineering supports model development and deployment\nFamiliarity with Python-based data analysis libraries such as Pandas or NumPy is a plus\nInterest in Generative AI, Large Language Models (LLMs), or AI-powered data solutions is desirable\nStrong analytical and problem-solving skills\nGood verbal and written communication skills\nAbility to learn quickly and adapt to new technologies\nAbility to work effectively in a fast-paced global environment\nEducation\nBachelor’s degree in Computer Science, Information Technology, Engineering, or a related field\nCorporate Security Responsibility\nAll activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:\nAbide by Mastercard’s security policies and practices;\n\nEnsure the confidentiality and integrity of the information being accessed;\n\nReport any suspected information security violation or breach, and\n\nComplete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.","description_format":"text","description_chars":6633,"description_truncated":false,"requirements":{"experience_years_min":1,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Cards & Card Issuing","Payment Processing & 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