{"id":1515894,"url":"https://alion.io/job/mastercard-director-data-engineering-3","title":"Director Data Engineering","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":92,"open_postings":146,"ghost_share":0.007,"stale_share":0.452,"repost_share":0.055,"time_to_fill_p50_days":21,"computed_at":"2026-10-03T05:45:00Z"}},"role":"Leadership","role_family":"Leadership","seniority":"head","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":57000,"max_usd":138000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":39},"experience_years_min":15,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Apache NiFi","optional":false},{"name":"AWS","optional":false},{"name":"Cassandra","optional":false},{"name":"CI/CD","optional":false},{"name":"Hadoop","optional":false},{"name":"Java","optional":false},{"name":"Master Data Management","optional":false},{"name":"Oracle","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-09-30T09:26:56Z","employer_posted_date":"2026-09-30","last_verified_at":"2026-10-04T02:13:19Z","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\nDirector Data EngineeringDirector, Data EngineeringData Collection & Engineering (DC&E)\nOverview\nMastercard powers a connected and inclusive digital economy by delivering secure, resilient, and intelligent payment technologies across the globe. Every day, Mastercard processes billions of payment interactions and generates massive volumes of transaction, customer, merchant, fraud, and operational data that power critical business decisions and innovative products.\nAs a Director, Data Engineering within the Data Collection & Engineering (DC&E) organisation, you will lead strategic data engineering initiatives that enable Mastercard's enterprise data ecosystem. You will be responsible for defining and executing the technology vision for large-scale Data Warehouse, Data Lakehouse, and Data Platform solutions supporting advanced analytics, AI, product innovation, regulatory reporting, and operational intelligence.\nThis role requires a combination of strong people leadership, executive stakeholder management, and deep technical expertise in modern data platforms, cloud-native architectures, distributed processing frameworks, and enterprise-scale data governance.\nThe ideal candidate will have a proven track record of building high-performing engineering organisations, driving large-scale cloud modernisation programmes, and delivering business outcomes through data at global scale.\nRole\nStrategic Leadership\nDefine and execute the long-term Data Engineering strategy aligned with Mastercard's AI, analytics, digital payments, and data platform roadmap.\nPartner with business, product, architecture, security, and technology leaders to translate strategic objectives into scalable data solutions.\nDrive organisational transformation initiatives involving cloud migration, platform modernisation, automation, and engineering excellence.\nDevelop multi-year roadmaps for data platform evolution, capacity growth, and technology investment planning.\nData Platform Architecture\nLead the architecture and implementation of highly scalable, secure, and resilient Data Lakehouse and Data Warehouse platforms.\nEstablish enterprise standards for data ingestion, transformation, storage, governance, lineage, metadata management, observability, and quality control.\nDrive adoption of reusable engineering frameworks and platform capabilities that enable self-service data products and accelerated delivery.\nEnsure architecture supports a \"Build Once, Deploy Anywhere\" model across on-premises, hybrid, and public cloud environments.\nCloud Modernisation & Engineering Excellence\nLead large-scale migration programmes moving enterprise data workloads from legacy platforms to cloud-native architectures.\nEstablish best practices for distributed processing, workflow orchestration, platform automation, and infrastructure optimisation.\nDrive adoption of modern DataOps, DevOps, CI/CD, and Infrastructure-as-Code practices across the engineering organisation.\nEstablish operational standards for platform resiliency, disaster recovery, performance engineering, and capacity management.\nEngineering Organisation Leadership\nBuild, lead, and develop high-performing teams comprising Managers, Principal Engineers, Lead Engineers, and Senior Data Engineers.\nFoster a culture of innovation, accountability, technical excellence, collaboration, and continuous learning.\nDrive workforce planning, succession management, talent acquisition, skills development, and employee engagement initiatives.\nProvide coaching and mentorship to technology leaders and senior engineering talent.\nDelivery & Stakeholder Management\nOversee delivery of multiple strategic programmes supporting Mastercard's analytics, data science, product development, fraud, and regulatory functions.\nManage complex stakeholder relationships across business units, executive leadership teams, and external partners.\nEnsure project execution aligns with business priorities, timeline commitments, financial objectives, and risk management standards.\nEstablish governance frameworks and operating models that improve delivery predictability and engineering productivity.\nInnovation & Emerging Technology\nEvaluate emerging technologies and define Mastercard's point of view on modern data engineering, AI-enabled data platforms, real-time analytics, and next-generation lakehouse architectures.\nSponsor proof-of-concept initiatives and technology evaluations that drive competitive advantage and business value.\nChampion adoption of GenAI-enabled engineering practices, metadata-driven frameworks, and intelligent automation.\nOperational Excellence\nEstablish engineering KPIs, SLAs, and platform health metrics to continuously improve service reliability and operational efficiency.\nLead resolution of high-severity production incidents and implement systemic improvements to prevent recurrence.\nEnsure compliance with Mastercard's security, privacy, regulatory, and engineering governance standards.\nAll About You\nLeadership Experience\n15+ years of experience delivering enterprise-scale Data Warehouse, Data Lake, Lakehouse, and Big Data solutions.\n7+ years of leadership experience managing engineering managers, architects, and distributed engineering teams.\nProven success leading global engineering organisations across multiple business domains and technology platforms.\nExperience managing large programmes involving multiple teams, stakeholders, vendors, and strategic initiatives.\nData Engineering Expertise\nDeep expertise designing and implementing large-scale data platforms using: Apache Kafka, Apache Spark, Scala/Java/Python, Hadoop ecosystem technologies and Distributed storage and compute architectures\nExtensive experience building: Enterprise Data Warehouses, Data Lakes, Lakehouse platforms, Real-time and batch processing frameworks, Enterprise metadata and governance platforms\nStrong understanding of: Data Modelling, Data Governance, Data Quality Management, Data Cataloguing, Data Lineage, Data Security and Master Data Management (MDM)\nCloud & Platform Engineering\nExtensive experience designing cloud-native architectures on AWS and hybrid cloud environments.\nStrong experience with: Amazon S3, EMR, Glue, Athena, EKS, Airflow, NiFi, Streaming and event-driven architectures\nExperience implementing:CI/CD pipelines, Infrastructure as Code, DataOps frameworks, Platform observability and monitoring solutions\nDatabase & Analytical Technologies\nStrong expertise with Relational and NoSQL technologies: Oracle, SQL Server, Cassandra and other Distributed databases\nAdvanced SQL optimisation and performance tuning skills.\nBusiness & Executive Leadership\nAbility to connect technology investments with measurable business outcomes.\nStrong executive communication and presentation skills.\nExperience influencing Vice Presidents, Senior Vice Presidents, and executive stakeholders.\n• Proven ability to balance innovation, delivery commitments, operational excellence, and financial accountability.\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":8100,"description_truncated":false,"requirements":{"experience_years_min":15,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Cards & Card Issuing","Payment Processing & Gateways"],"lifecycle":[{"event":"open","at":"2026-09-30T09:26:56Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring 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