{"id":104603,"url":"https://alion.io/job/mastercard-lead-data-engineer-2","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":86,"open_postings":177,"ghost_share":0.017,"stale_share":0.492,"repost_share":0.079,"time_to_fill_p50_days":27,"computed_at":"2026-11-06T05:58:05Z"}},"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":68000,"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":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"Go","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Java","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"Terraform","optional":false},{"name":"Airflow","optional":true},{"name":"Dimensional Modeling","optional":true},{"name":"Docker","optional":true},{"name":"Dynatrace","optional":true},{"name":"Gatling","optional":true},{"name":"GDPR","optional":true},{"name":"GitHub Actions","optional":true},{"name":"IAM","optional":true},{"name":"Jenkins","optional":true},{"name":"JMeter","optional":true},{"name":"JUnit","optional":true},{"name":"Kubernetes","optional":true},{"name":"PCI DSS","optional":true},{"name":"Prometheus","optional":true},{"name":"Splunk","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-08-20T00:00:00Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-11-07T04:02:51Z","board_verified":true,"closed_at":null,"days_open":79,"trust":{"level":"ok","repost_count":2,"flags":["repost"],"days_open":78},"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 EngineerWho is Mastercard?Mastercard 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.\nRole Overview\nData Platform & Orchestration is seeking a Lead Data Engineer to design and build next-generation, cloud-native data platforms supporting Mastercard’s global data ecosystem.\nIn this role, you will lead the development of scalable batch and real-time data pipelines, enabling efficient data processing across Data Lakes and Data Warehouses. You will work at the intersection of data engineering, cloud platforms, and distributed systems, contributing to high-impact initiatives and driving engineering excellence.\nThis role is ideal for someone who thrives in a fast-paced, collaborative environment, enjoys solving complex data challenges, and is passionate about building resilient, high-performance systems at scale.\nKey Responsibilities\nDesign and build scalable batch and real-time data pipelines using Spark, Kafka, and (preferred) Apache Flink\nDevelop robust ETL/ELT frameworks for structured and unstructured data\nBuild and optimize data ingestion and transformation pipelines for Data Lakes and Data Warehouses\nImplement stream processing solutions for near real-time use cases\nEnsure data quality, lineage, observability, and governance across pipelines\nOptimize data jobs for performance, scalability, and cost efficiency\nDesign and operate cloud-native data platforms on AWS, Azure, or GCP\nLeverage managed services such as S3/ADLS/GCS, EMR/Databricks, BigQuery/Redshift/Snowflake\nImplement Infrastructure as Code (Terraform, CloudFormation, or equivalent)\nEnsure high availability, fault tolerance, and disaster recovery\nDrive cost optimization strategies for large-scale data workloads\nImplement secure data access controls aligned with enterprise standards\nPlatform & Engineering Excellence\nBuild reusable data frameworks, libraries, and pipeline templates\nDrive adoption of CI/CD, automated testing, and observability\nDevelop and enhance developer tooling and platform capabilities\nContribute to cloud-agnostic platform architecture and automation\nTechnical Leadership & Collaboration\nProvide technical leadership, mentorship, and design guidance\nConduct code reviews, architecture reviews, and best practice enforcement\nCollaborate with architects, product owners, and cross-functional teams\nAct as a Subject Matter Expert (SME) for data platform initiatives\nPromote engineering excellence through documentation, design standards, and innovation\nWork effectively across globally distributed teams\nRequired Skills & Qualifications\nStrong proficiency in Object-Oriented Programming and Design (OOP/OOAD) Java (JDK 8+); Python and/or Go is a plus\nExperience building data services and distributed systems\nStrong understanding of multithreading, scalability, and performance tuning\nStrong hands-on experience with AWS, Azure, or GCP\nExperience with cloud-native data services (S3, ADLS, GCS, Databricks, EMR, BigQuery, Redshift)\nStrong experience with Apache Spark (Core, SQL, Structured Streaming)\nHands-on experience with Kafka or equivalent messaging platforms\nExperience with real-time processing frameworks (Apache Flink preferred or Spark Streaming)\nStrong understanding of ETL/ELT design patterns and pipeline architectures\nExperience with data formats (Parquet, Avro, ORC)\nKnowledge of data modeling (dimensional modeling, star/snowflake schemas)\nProficiency in Infrastructure as Code (Terraform, CloudFormation, ARM templates)\nExperience with Docker and Kubernetes\nSolid understanding of cloud networking, IAM, and security best practices\nExperience with workflow orchestration tools (Airflow or equivalent)\nStrong SQL skills and experience with Data Warehouse platforms\nUnderstanding of data governance, lineage, and observability frameworks\nExperience with CI/CD tools (Jenkins, GitHub Actions, etc.)\nStrong testing practices (JUnit or equivalent frameworks)\nExperience with monitoring & observability (Splunk, Dynatrace, Prometheus, etc.)\nFamiliarity with performance testing tools (JMeter, Gatling)\nUnderstanding of secure development practices (PCI DSS, GDPR, etc.)\nProven ability to lead and mentor engineering teams\nStrong problem-solving and system design skills\nPassion for innovation, automation, and continuous improvement\nAbility to operate effectively in a fast-paced, global environment\nEducation\n• Bachelor’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 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