{"id":3061912,"url":"https://alion.io/job/mastercard-senior-data-engineer-16","title":"Senior 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":86,"open_postings":170,"ghost_share":0.024,"stale_share":0.435,"repost_share":0.082,"time_to_fill_p50_days":26,"computed_at":"2026-10-23T05:54:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","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":23000,"max_usd":46000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":71},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Machine Learning","optional":false},{"name":"Platform Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-22T06:48:54Z","employer_posted_date":"2026-10-22","last_verified_at":"2026-10-23T15:29:03Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"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\nSenior Data EngineerOverviewThe Data Engineering team builds trusted, scalable datasets and pipelines that power analytics, BI, and machine learning use cases across Mastercard. This role will help design and deliver resilient data pipelines, curated data models, and ML-ready feature datasets while partnering closely with platform engineering, data science, and BI stakeholders.\nRole\nAs a Data Engineer / MLE, you will:\nDesign, build, and maintain scalable batch and near-real-time data pipelines.\nDevelop curated datasets and data models that enable reliable analytics and ML workloads.\nImplement pipeline reliability patterns (monitoring, alerting, retries, performance tuning).\nPartner with data scientists to enable feature engineering and model operationalization.\nEnsure secure data handling aligned to enterprise governance and compliance expectations.\nDrive engineering best practices (code quality, testing, documentation, CI/CD where applicable).\nAll About You\nEssential Skills (Must Have):\nStrong proficiency in SQL and Python (or Scala) for data engineering.\nExperience building data pipelines using distributed processing (e.g., Spark,PySpark,HADOOP).\nExperience in using data technology technology like AWS, S3, Databricks.\nSolid understanding of data modeling (dimensional and/or lakehouse patterns) and data quality concepts.\nExperience working with cloud data ecosystems (AWS preferred) and object storage / lake patterns.\nAbility to troubleshoot performance and reliability issues in production pipelines.\nStrong communication skills and ability to collaborate across engineering and analytics stakeholders.\nNice to have:\nExperience with Databricks or similar lakehouse platforms.\nExposure to ML feature pipelines, model deployment patterns, or MLOps concepts.\nExperience in payments / banking / regulated environments.\n• Familiarity with data governance tooling (catalog, lineage) and PII handling patterns.\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":3052,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Cards & Card Issuing","Payment Processing & Gateways"],"lifecycle":[{"event":"open","at":"2026-10-22T06:48:54Z"}],"visa":[],"liveness":{"score":99,"band":"hot","label":"Hiring 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