Python Developer | Cloud Infrastructure
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AI Summary
Support and operate large-scale data infrastructure systems while improving reliability through automation and monitoring. Build and enhance Python-based tooling to streamline operational workflows and maintain technical documentation.
Who We Are
At MAS Global Consulting, we combine top-tier engineering talent with a people-first culture to help leading organizations accelerate digital transformation. Our teams deliver modern, high-quality solutions across cloud, data, AI, and platform engineering while fostering continuous growth and collaboration.
We proudly partner with Affirm, a world-class fintech known for engineering excellence and a strong culture of innovation. Through this role, you will join Affirm’s Data and Storage Services (DSS) organization—an engineering group responsible for powering mission-critical data infrastructure at massive scale.Who You Are
You are a Backend / Infrastructure Engineer with strong experience in Python and cloud-native ecosystems. You excel at supporting large-scale distributed systems and enjoy solving operational challenges through automation, tooling, and modern DevOps practices.
You thrive in environments where you collaborate across multiple teams, communicate clearly, and take end-to-end ownership of technical problems. You are proactive, analytical, and committed to improving reliability, observability, and efficiency.
What You’ll Do
Must-Have Qualifications
At MAS Global Consulting, we combine top-tier engineering talent with a people-first culture to help leading organizations accelerate digital transformation. Our teams deliver modern, high-quality solutions across cloud, data, AI, and platform engineering while fostering continuous growth and collaboration.
We proudly partner with Affirm, a world-class fintech known for engineering excellence and a strong culture of innovation. Through this role, you will join Affirm’s Data and Storage Services (DSS) organization—an engineering group responsible for powering mission-critical data infrastructure at massive scale.Who You Are
You are a Backend / Infrastructure Engineer with strong experience in Python and cloud-native ecosystems. You excel at supporting large-scale distributed systems and enjoy solving operational challenges through automation, tooling, and modern DevOps practices.
You thrive in environments where you collaborate across multiple teams, communicate clearly, and take end-to-end ownership of technical problems. You are proactive, analytical, and committed to improving reliability, observability, and efficiency.
What You’ll Do
- Support and operate large-scale data infrastructure systems across OLTP/OLAP, Streaming, and Batch workloads.
- Improve infrastructure reliability through automation, monitoring, and incident response.
- Build and enhance Python-based tooling and services to streamline operational workflows.
- Maintain and modernize Affirm’s Python ecosystem, ensuring compatibility with supported versions and dependencies.
- Automate workflows to improve collaboration, visibility, and operational efficiency across teams.
- Handle internal stakeholder questions and escalations with clear, timely, technical responses.
- Create and maintain technical documentation, including runbooks, onboarding guides, and monitoring dashboards.
Must-Have Qualifications
- Strong programming experience in Python or Java.
- Hands-on experience operating cloud infrastructure, particularly AWS and Kubernetes/Docker.
- Proven track record maintaining large-scale distributed systems in production.
- Excellent communication skills and ability to collaborate with engineering and product teams.
- Strong technical writing skills (documentation, runbooks, user guides).
- Experience with streaming systems such as Flink or Kafka.
- Familiarity with data platform technologies like Spark, Data Lake, MySQL, Snowflake.
- Experience with data processing frameworks and near-real-time pipelines.
- Experience supporting shared infrastructure services across multiple engineering teams.
- Familiarity with using LLMs or AI tools to enhance automation and scale operational support.
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