Lead Data Engineer

About the role

Mastercard is seeking a Lead Data Engineer to design, build, and scale next‑generation data platforms that support enterprise‑wide analytics, BI, and regulatory reporting. You will drive cloud‑native transformations and mentor a team of engineers.

Key responsibilities

• Design, develop, test, and deploy secure, scalable data pipelines using Apache Spark, Scala/Java on Hadoop and cloud object storage.
• Build batch and near‑real‑time processing frameworks for petabyte‑scale workloads.
• Implement “build once, run anywhere” architecture across on‑prem and public cloud environments.
• Lead end‑to‑end development, from requirement analysis to production support, and mentor junior engineers.
• Drive migration of legacy ETL workloads to AWS services such as S3, EMR, and Glue.

Required profile

• 10‑12 years of experience delivering enterprise‑scale Data Warehouse, Data Lake or Lakehouse solutions.
• Proven track record of leading large‑scale data engineering projects in distributed computing environments.
• Strong analytical, problem‑solving and communication skills, with experience in Agile delivery.

Required skills

• Apache Spark, Scala, Java
• Hadoop ecosystem
• Apache Airflow or Apache NiFi
• SQL, Oracle, SQL Server, Cassandra, DynamoDB
• AWS services: Amazon S3, EMR, AWS Glue