Netskrt is looking to hire a Director of Engineering (Analytics) to lead our analytics and ML initiatives from the ground up and empower our teams to get the most insight from data. You are passionate about data-driven innovation, especially at scale. This position is located in our beautiful downtown office in Vancouver, BC located next to the Burrard SkyTrain station. This is a hybrid role with 2 days in office.
We are a global Content Delivery Network (CDN) company building the future of intelligent traffic management. Netskrt’s Last-Mile CDN service consists of three major components: intelligent content collection, staging and distribution; adaptive networking, leveraging connectivity as and when available; and an edge cache that is deployed into last-mile ISPs and private network locations for the delivery of content to consumers.
You will work alongside a group of passionate engineers and data scientists in a truly collaborative environment and help shape the technical direction of a high-impact, greenfield initiative at a leader in CDN technology.

REQUIRED QUALIFICATIONS:

• Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field
• Deep experience leading engineering teams in data, analytics, or ML environments (preferably at scale).
• Expert knowledge of distributed data processing (Kafka, Spark, ClickHouse or similar).
• Proven track record of architecting systems processing terabytes or more of data daily.
• Strong background in ML/AI for operational systems or network optimization is a huge plus.
• Experience building and mentoring diverse, high-performing teams.

KEY SKILLS:

• AI/ML
• Big Data
• Kafka
• Spark
• Superset
• Clickhouse
• ETL pipelines

GOOD TO KNOW:

• Competitive compensation depending on experience
• Health benefits on Day 1
• Stock options
• Highly collaborative environment
• Sut/Stand desks
• Office snacks and monthly socials
• Secure bike room in office building
• Gym in office building

• Lead a high-performance engineering team focused on ML-driven traffic optimization and analytics.
• Architect scalable data pipelines leveraging Kafka, ClickHouse, and Spark to process terabytes of access logs daily.
• Collaborate closely with product, platform, and leadership teams to define and execute our analytics and ML strategy.
• Drive the development and deployment of machine learning algorithms to optimize real-time CDN traffic management.