Software Engineer II, Data Engineer

Responsibilities

• System Ownership: Build and maintain a comprehensive understanding across multiple complex data pipelines and platform projects.
• Core Data Engineering: Design, develop, test, and deploy robust backend services and data pipelines processing terabytes of advertising and ACR data.
• Platform & Governance: Build and maintain internal platform tooling to enforce strict Data Governance, Data Quality, and Data Compliance standards.
• Task Definition & Scoping: Autonomously define the scope, technical enhancements, and deliverables for features of limited complexity, and provide accurate time estimates.
• Feature Set Contribution: Effectively contribute to the planning and development of features affecting multiple components across our data ecosystem with minimal guidance.
• Advanced Debugging: Independently troubleshoot, debug, and resolve somewhat complex bugs within distributed environments and massive-scale data processing workflows.
• Technical Communication: Comprehend and clearly communicate complex technical concepts—including technical designs, system architecture, and key engineering decisions—to both technical and non-technical stakeholders.
• Global Collaboration: Work closely with product managers, data scientists, and engineering counterparts in the US and India (requiring overlap with US time zones, typically aligning with core hours of 8 AM - 11 AM MST).

Requirements

• Bachelor's Degree in Computer Science, Engineering, or a related technical field.
• 1 to 2 years of relevant professional software development experience, with a strong preference for Backend or Data Engineering roles.
• Strong proficiency in Data Structures and Algorithms.
• Solid understanding of core Computer Science concepts, specifically Operating Systems, Computer Networks, and DBMS.
• Exceptional problem-solving and analytical skills, with a proactive, self-starter attitude.
• Clear and effective communication of technical challenges, both verbally and in writing.
• Demonstrated ability to collaborate effectively across time zones.

Preferred Experience

• With Big Data processing frameworks, specifically Apache Spark (PySpark or Scala-Spark).
• Hands-on experience with modern data platforms like Databricks and orchestration tools like Apache Airflow.
• Experience building, maintaining, and scaling complex ETL processes.
• Familiarity with cloud computing platforms (AWS, GCP, or Azure) and related infrastructure.
• Understanding of distributed systems concepts and proficiency in Low-Level Design (LLD).