Lead, Data Engineer

You’ll join Mastercard’s AI Ops team to design, build, and evolve data solutions that power operational visibility and intelligent decision‑making. This technical leadership role drives scalable pipelines, ensures data quality and security, and mentors engineers while shaping the ONE Data Lake vision. What You'll Do Lead design and delivery of scalable data pipelines for AI Ops, SRE, and engineering. Conduct code reviews, enforce engineering standards, and ensure solution quality. Create and maintain documentation for requirements, designs, tests, and deployment plans. Monitor data quality, security, observability, and resiliency across pipelines. Contribute to roadmap planning, modernization, and innovation for the ONE Data Lake. Operationalize machine‑learning models and support their deployment in production. What You Need Deep experience building and operating scalable pipelines on cloud or enterprise platforms. Hands‑on expertise with modern orchestration tools (e.g., Airflow) and data platforms like Cloudera. Proven ability to lead technical design, code reviews, and set engineering standards. Strong communication skills for stakeholder influence and clear technical documentation. Experience mentoring engineers and driving cross‑functional collaboration. Knowledge of data security, monitoring, and observability best practices. Good to Have Experience with Cloudera data onboarding and ecosystem. Familiarity with ML engineering tasks such as model serving. Exposure to AI Ops dashboards, reports, and alerting mechanisms. The Opportunity The role sits at the core of the AI Ops team, creating dashboards and alerts that drive data‑driven decisions, and is pivotal to delivering Mastercard’s ONE Data Lake initiative.