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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:
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Programming Languages: Expert-level proficiency in Python and at least one strongly typed, object-oriented language (Rust, C++, or Go)
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Data Platforms: Hands-on experience with Snowflake for data warehousing and analytics
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Big Data Processing: Proven experience with PySpark or Scala on Databricks/Apache Spark used for high-volume, streaming data processing
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Data Engineering: Strong background in building and maintaining data pipelines, ETL processes, and data architecture
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Container Technologies: Minimum 5 years of hands-on experience with Docker and Kubernetes, including AWS implementations (EKS, ECS, Fargate)
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Cloud Platform: Required experience working in AWS environment with deep understanding of core services and best practices
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Ad Technology: Deep understanding of programmatic advertising, RTB (Real-Time Bidding), DSPs, SSPs, or related ad tech systems
Preferred Qualifications:
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Machine Learning & AI: Experience building ML pipelines, particularly those involving LLMs, generative AI, or other advanced ML techniques
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Advanced AWS Services: Experience with additional AWS services such as Lambda, Step Functions, EMR, Redshift, or SageMaker
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Infrastructure as Code: Proficiency with Terraform, CloudFormation, or similar IaC tools
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Streaming Data: Knowledge of real-time data processing frameworks (Kafka, Kinesis, Pulsar)
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Database Technologies: Experience with both SQL and NoSQL databases
Experience & Leadership:
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Experience: 8-15 years of software engineering experience, with 10-12 years being the target range
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Leadership: Demonstrated ability to lead technical projects and mentor junior team members
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Communication: Excellent written and verbal communication skills
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Problem Solving: Strong analytical and problem-solving capabilities with attention to detail
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