Overview We are seeking an exceptional Senior Principal Engineer to join our Engineering team. This role combines deep technical expertise in data engineering with leadership responsibilities in a high-impact environment. The ideal candidate will architect and build scalable systems that power our cutting-edge advertising AI platform while mentoring the next generation of engineers.
Key Responsibilities Technical Leadership : Design and implement large-scale data engineering pipelines that process billions of ad events daily; Architect robust, high-performance systems using modern data stack technologies; Support the development of machine learning pipelines incorporating LLMs and generative AI for ad optimization and targeting; Drive technical decisions across multiple teams and projects; Establish engineering best practices and standards for the ad technology platform
System Development : Build and optimize data processing systems using Snowflake and Databricks / Spark; Develop high-performance backend services in Python and at least one systems programming language; Create scalable ETL / ELT pipelines for real-time and batch processing; Implement monitoring, alerting, and observability solutions for production systems; Ensure system reliability, performance, and security across all platforms
Project Leadership & Mentorship : Lead cross-functional projects from conception through delivery; Mentor junior and mid-level engineers, providing technical guidance and career development support; Collaborate with architects, product managers, data scientists, and other stakeholders to translate business requirements into technical solutions; Conduct code reviews and provide constructive feedback to maintain code quality; Present technical concepts and project updates to both technical and non-technical audiences
Required Qualifications Technical Skills : Expert-level proficiency in Python and at least one strongly typed, object-oriented language (Rust, C++, or Go)
Data Platforms : Hands-on experience with Snowflake for data warehousing and analytics
Big Data Processing : Proven experience with PySpark or Scala on Databricks / Apache Spark used for high-volume, streaming data processing
Data Engineering : Strong background in building and maintaining data pipelines, ETL processes, and data architecture
Container Technologies : Minimum 5 years of hands-on experience with Docker and Kubernetes, including AWS implementations (EKS, ECS, Fargate)
Cloud Platform : Required experience working in AWS environment with deep understanding of core services and best practices
Ad Technology : Deep understanding of programmatic advertising, RTB (Real-Time Bidding), DSPs, SSPs, or related ad tech systems
Preferred Qualifications Machine Learning & AI : Experience building ML pipelines, particularly those involving LLMs, generative AI, or other advanced ML techniques
Advanced AWS Services : Experience with additional AWS services such as Lambda, Step Functions, EMR, Redshift, or SageMaker
Infrastructure as Code : Proficiency with Terraform, CloudFormation, or similar IaC tools
Streaming Data : Knowledge of real-time data processing frameworks (Kafka, Kinesis, Pulsar)
Database Technologies : Experience with both SQL and NoSQL databases
Experience & Leadership Experience : 8-15 years of software engineering experience, with 10-12 years being the target range
Leadership : Demonstrated ability to lead technical projects and mentor junior team members
Communication : Excellent written and verbal communication skills
Problem Solving : Strong analytical and problem-solving capabilities with attention to detail
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Recruiting Is Hiring • New York, NY, United States