{"id":3343368,"url":"https://alion.io/job/mastercard-lead-data-engineer-10","title":"Lead Data Engineer","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":189,"ghost_share":0.016,"stale_share":0.423,"repost_share":0.079,"time_to_fill_p50_days":27,"computed_at":"2026-11-01T06:10:25Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","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":31000,"max_usd":67000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":20},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"Java","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Scrum","optional":false},{"name":"Spark","optional":false},{"name":"Amazon EC2","optional":true},{"name":"Amazon S3","optional":true},{"name":"Apache Kafka","optional":true},{"name":"AWS Lambda","optional":true},{"name":"ETL/ELT","optional":true},{"name":"Hadoop","optional":true},{"name":"IAM","optional":true},{"name":"Informatica","optional":true}],"status":"live","first_seen_at":"2026-10-26T00:00:00Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-11-01T10:15:32Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"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\nLead Data EngineerPosition OverviewHave you ever wanted to be part of something BIG?\nNow is the time to make an immediate impact at a leading global technology company, Mastercard.\nThis role is part of the AI&DPE Data Engineering platform team, responsible for building and evolving large scale backend data systems, real time and batch pipelines, and AI enabled services that power analytics, decisioning, and automation across the organization.\nThis is a backend engineering role, focused on Scala/Python/Java, distributed data platforms (Cloudera/Spark), and cloud based architectures, with a strong emphasis on AI agent creation and intelligent automation. Visualization tools (e.g., Qlik) are consumers of the platform, not the core focus of this role.\nYou will work with massive transactional datasets, modern big data and cloud platforms, and AI driven workflows to transform how Mastercard processes, enriches, and operationalizes data at global scale.\nPRIMARY RESPONSIBILITIES\nBackend & Data Platform Engineering\nDesign, develop, and maintain backend services and data pipelines using Scala, Python and Java\nBuild and optimize batch and streaming workloads on Cloudera Data Platform (CDP) using Spark\nWork with Cloudera Manager to support platform configuration, monitoring, performance tuning, and operational stability\nDesign and implement high quality datamarts and curated datasets with strong emphasis on data integrity, performance, and reliability\nAI Agents & Intelligent Automation\nDesign, build, and integrate AI powered agents that operate to support:\nAnomaly detection and operational intelligence\nworkflow automation\nApply generative AI driven, or rule based agents to reduce manual effort and improve scalability across backend systems\nCloud & Modern Data Architecture\nBuild and support data and compute workloads in AWS environments\nLeverage Databricks for large scale data processing, advanced analytics\nContribute to cloud native and hybrid architectures integrating on prem and cloud platforms\nIntegration & Downstream Enablement\nEnable downstream consumers (analytics, visualization, reporting tools such as Qlik) through well designed, reliable backend data interfaces\nPartner with analytics, fraud, and business teams to ensure backend systems meet evolving needs without compromising platform stability\nDocumentation & Collaboration\nCreate clear technical documentation, including architecture diagrams, data flows, and design specifications\nParticipate in Agile/Scrum ceremonies and cross functional design reviews\nMentor and upskill team members in backend engineering, big data, and AI agent concepts\nKNOWLEDGE AND SKILL REQUIREMENTS\nRequired\nBS/BA degree in Computer Science, Engineering, Information Systems, or related field\nStrong handson experience with Scala,Python/Java in backend or data intensive systems\nExperience working with Cloudera Data Platform (CDP) and Spark\nFamiliarity with Cloudera Manager for cluster administration, monitoring, or troubleshooting\nStrong understanding of data modeling concepts, distributed systems, and large scale data processing\nExcellent problem solving skills and ability to work independently in complex environments\nGOOD TO HAVE / STRONGLY PREFERRED\nHands on experience building, integrating, or supporting AI driven agents or intelligent automation solutions\nExperience with Databricks for data engineering or ML workloads\nExperience working in AWS (e.g., S3, EC2, EMR, Glue, Lambda, IAM, or equivalent services)\nKnowledge of streaming and big-data technologies:\nKafka\nHadoop ecosystem\nHive/Impala\nExposure to model monitoring, or AI platform enablement\nExperience with ETL tools such as Informatica\nExperience working in Agile / Scrum teams within large enterprises\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 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