Integral Ad Science (IAS) is a global leader in digital media quality. IAS makes every impression count, ensuring that ads are viewable by real people, in safe and suitable environments, activating contextual targeting, and driving supply path optimization.

Our mission is to be the global benchmark for trust and transparency in digital media quality for the world’s leading brands, publishers, and platforms. We do this through data-driven technologies with actionable real-time signals and insight. Founded in 2009 and headquartered in New York, IAS works with thousands of top advertisers and premium publishers worldwide. For more information, visit integralads.com or email us at careers@integralads.com.

As a Staff Data Engineer you will design, implement, and maintain big data pipelines responsible for aggregating tens of billions of daily transactions. You will be part of a growing team to develop and mature  IAS’ capability in video ad verification, analytics and anti ad fraud software products.

What you’ll get to do:

• Architect, design, code and maintain components for aggregating tens of billions of daily transactions

• Work on Big Data technologies such as Hadoop, MapReduce, Kafka, and/or Spark in columnar databases on AWS

• Contribute to the entire software lifecycle including hands-on development, code reviews, testing, deployment, and documentation for streaming & batch ETL and RESTful APIs

• Provide leadership, work collaboratively, and be a mentor in an awesome team

You should apply if you have most of this:

• Bachelors or Masters in Computer Engineering, Computer Science, Electrical Engineering or related field

• 8+ years of recent hands-on experience with Java

• 8+ years of experience designing and building data pipelines and data-intensive applications

• Experience using Big Data frameworks (e.g., Hadoop, Spark) , databases (e.g., RedShift, Snowflake) for complex data assembly and transformation

• Strong knowledge of collections, multi-threading, JVM memory model, etc.

• In-depth understanding of algorithms, performance, scalability, and reliability in a Big Data setting

• Solid understanding of OLTP and OLAP systems, database fundamentals

• Solid knowledge of SQL

• Experience in full software development, Agile, and CI/CD

• Experience building production level systems in a cloud environment (AWS, Azure or GCP)

What puts you over the top:

• Orchestrating data pipelines using tools such as Airflow

• Familiarity with messaging frameworks like Kafka or RabbitMQ

• Experience with Spark streaming or Flink