{"id":1558918,"url":"https://alion.io/job/mastercard-lead-data-engineer-6","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":92,"open_postings":146,"ghost_share":0.007,"stale_share":0.452,"repost_share":0.055,"time_to_fill_p50_days":21,"computed_at":"2026-10-02T05:45:00Z"}},"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":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":27000,"max_usd":49000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":16},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Airflow","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache NiFi","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"Cassandra","optional":false},{"name":"DynamoDB","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Hadoop","optional":false},{"name":"Java","optional":false},{"name":"Oracle","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-09-30T00:00:00Z","employer_posted_date":"2026-09-30","last_verified_at":"2026-10-02T03:24:22Z","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\nLead Data EngineerOverviewMastercard powers the global economy by enabling secure, seamless, and intelligent payments across the world. Behind every transaction is a sophisticated technology ecosystem that processes billions of payment events with speed, resilience, and precision.\nAs a Lead Data Engineer within the Data Collection & Engineering (DC&E) organisation, you will play a critical role in designing, building, and scaling Mastercard's next-generation data platforms and analytical ecosystems. You will develop high-performance, cloud-enabled data pipelines that power Mastercard's enterprise data warehouse and lakehouse environments, enabling advanced analytics, business intelligence, regulatory reporting, and data-driven decision making across the organisation.\nThis role offers a unique opportunity to solve large-scale data engineering challenges, work with cutting-edge big data technologies, and contribute to a modern cloud transformation programme supporting global payment processing platforms.\nKey Responsibilities\nData Engineering & Development\nDesign, develop, test, and deploy high-quality, secure, scalable, and resilient data pipelines using Apache Spark, Java/Scala across Hadoop and cloud-native object storage platforms.\nBuild and maintain batch and near real-time data processing frameworks capable of supporting petabyte-scale workloads.\nDevelop reusable engineering components and frameworks that accelerate data product delivery while maintaining enterprise standards.\nArchitecture & Platform Engineering\nDesign and implement a \"build once, run anywhere\" architecture supporting seamless deployment across on-premises and public cloud environments without code changes.\nImplement data lineage, metadata management, data cataloguing, data quality controls, and observability capabilities across the data ecosystem.\nCollaborate with architects and platform teams to establish scalable design patterns and engineering best practices.\nCloud Modernisation\nContribute to migration initiatives moving legacy ETL and data warehouse workloads from on-premises environments to cloud-native architectures.\nLeverage cloud services such as Amazon S3, EMR, Glue, and related data services to improve scalability, reliability, and operational efficiency.\nDrive adoption of modern lakehouse and distributed compute architectures.\nDelivery & Technical Leadership\nLead end-to-end development activities including requirement analysis, solution design, coding, testing, deployment, and production support.\nMentor and guide junior engineers through code reviews, technical coaching, and engineering best practices.\nPartner with product owners, analysts, architects, and business stakeholders to deliver high-quality solutions within committed timelines.\nOperational Excellence\nTroubleshoot complex production incidents and perform root cause analysis to identify and implement long-term remediation strategies.\nEnsure compliance with Mastercard's engineering, security, quality assurance, and operational governance standards.\nContinuously identify opportunities to improve performance, automation, monitoring, and process efficiency.\nInnovation\nEvaluate emerging data technologies and conduct proof-of-concept (POC) initiatives to determine their applicability within Mastercard's data ecosystem.\nContribute to engineering innovation and continuous improvement initiatives across the organisation.\nQualifications\nRequired Experience\n10-12 years of experience delivering enterprise-scale Data Warehouse, Data Lake, or Data Lakehouse solutions.\nProven experience implementing multiple end-to-end data engineering projects within large-scale distributed computing environments.\nHands-on experience migrating ETL and analytics workloads from on-premises platforms to cloud-native environments.\nTechnical Expertise\nStrong development experience using:Apache Spark, Scala or Java, Hadoop ecosystem technologies, Object Storage platforms\nExperience building orchestration and workflow solutions using: Apache Airflow/ Apache NiFi and Similar enterprise scheduling frameworks\nStrong SQL expertise and experience with Relational and NoSQL database technologies: Oracle/ SQL Server, Cassandra, Dynamo DB etc.\nWorking knowledge of cloud platforms, preferably AWS: Amazon S3, EMR, AWS Glue, Cloud-native data services\nProfessional Skills\nStrong analytical and problem-solving capabilities.\nExperience operating within Agile delivery environments.\nExcellent written and verbal communication skills.\nProven ability to collaborate within geographically distributed and matrix-based teams.\nSelf-starter with strong ownership, accountability, and execution focus.\n• Ability to learn emerging technologies quickly and apply them effectively to business challenges.\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":5887,"description_truncated":false,"requirements":{"experience_years_min":10,"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":"2026-10-01T03:18:32Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":2,"expected_fill_days":21,"reasons":["conf:2","velocity","win:early","comp:brand"],"computed_at":"2026-10-02T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/mastercard-lead-data-engineer-6","json_url":"https://alion.io/job/mastercard-lead-data-engineer-6.json","meta":{"generated_at":"2026-10-03T03:27:39Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3207,"day_limit":5000,"remaining_today":1793,"minute_limit":60,"resets_at":"2026-10-04T00:00:00Z"}}}