Senior Software Engineer, Data Platforms

Expectations (In this role, you will)

• Design, build, and scale the core data platform infrastructure that powers ingestion, processing, and data availability across Mudflap systems.
• Develop production-grade Python services, libraries, and frameworks used by engineers and data teams to reliably build and operate data pipelines.
• Architect scalable systems for high-throughput data ingestion, processing, and storage across batch and streaming workloads.
• Own the reliability, scalability, and performance of the data platform, ensuring systems meet production-grade standards for observability, fault tolerance, and operational excellence.
• Build and maintain platform abstractions, tooling, and infrastructure that simplify how engineering teams produce, transform, and consume data.
• Design platform-level capabilities for orchestration, pipeline execution, schema management, and data processing frameworks.
• Collaborate closely with backend, product, and analytics engineers to ensure the platform supports both operational and analytical workloads.
• Lead system design efforts for large-scale data infrastructure, making architectural decisions that support long-term platform scalability.
• Establish engineering best practices around Python development, system reliability, infrastructure ownership, and platform maintainability.
• Mentor engineers through design reviews, technical guidance, and best practices for building robust platform systems.

Experience (What we look for)

• Bachelor’s or Master’s degree in Computer Science (or related technical field)
• 8+ years of software engineering experience, with significant experience building infrastructure or platform systems.
• Expert-level proficiency in Python, with a track record of developing production-grade systems and frameworks.
• Strong command of SQL, with the ability to design scalable, performant, and reusable data components.
• Experience building distributed systems and large-scale data processing infrastructure.
• Deep understanding of system design, scalability, and performance optimization for data-intensive platforms.
• Experience building or operating data platforms, pipeline frameworks, or internal developer infrastructure.
• Strong experience with cloud infrastructure (AWS, GCP, or similar) and modern infrastructure tooling.
• Familiarity with data processing technologies and storage systems (e.g., Spark, Kafka, Snowflake, BigQuery, or similar).
• Experience designing reliable pipeline infrastructure and building systems that support high-throughput data ingestion and processing.
• Strong engineering ownership mindset with experience building, operating, and maintaining production infrastructure.
• Excellent communication skills and ability to collaborate with engineering teams to design scalable platform solutions.