Senior Data Engineer-1

Join a global payments technology leader to design, build, and operate high‑scale data pipelines that power secure, smart transactions. You’ll work hands‑on with cutting‑edge tools like Databricks, Spark, and dbt, delivering both batch and real‑time solutions for a rapidly growing fintech marketplace. What You'll Do Design and deliver batch and real‑time pipelines with Databricks, Spark, Python, PySpark. Build dbt transformation layers using test‑driven development and modular design. Create CI/CD workflows in GitLab/Jenkins and promote DataOps practices. Administer Databricks assets, optimize performance, manage access and cost. Implement data observability: quality, freshness, lineage, anomaly detection. Develop streaming solutions using Kafka and Spark Structured Streaming. Mentor engineers, conduct code and design reviews. What You Need Bachelor’s degree in CS or related field (Master’s a plus). 5+ years of data engineering experience. Deep expertise in Databricks, Spark, Python, and PySpark. Proven use of dbt with test‑driven development. Strong CI/CD skills with GitLab and Jenkins; DataOps knowledge. Experience building real‑time streaming pipelines (Kafka, Structured Streaming). Expert SQL and cloud platform experience (AWS, Azure, or GCP). Good to Have Experience in banking, e‑commerce, credit‑card or payment‑processing domains. Exposure to both SaaS and on‑premises architectures. Degree in mathematics, quantitative science, or related discipline. The Opportunity The role offers end‑to‑end ownership of complex data pipelines in a small, agile fintech team, allowing you to shape Mastercard’s cloud strategy while mentoring fellow engineers.