Senior Data Engineer - Ads Measurement

It takes powerful technology to connect our brands and partners with an audience of hundreds of millions of people. Whether you’re looking to write mobile app code, engineer the servers behind our massive ad tech stacks, or develop algorithms to help us process trillions of data points a day, what you do here will have a huge impact on our business—and the world.

A Little About Us:
We are an industry leading direct to Consumer and Ad tech solution for advertisers and publishers. Our innovative Ad tech gives one stop access to Yahoo, inc. trusted data, high quality inventory and demand, creative ad experiences and industry-leading machine learning, at global scale. Consumer Monetization team’s charter is to Find, Evaluate, Build, and Scale new monetization, subscription and internal campaign tools and products, ad formats and functionalities across all Yahoo brands including Yahoo Homepage, Yahoo Sports, Yahoo Finance, Yahoo News and AOL. This team is uniquely positioned to identify growth and revenue generation opportunities, design and implement solutions across consumer products and advertising platforms including video, display, native, and search.
 

A Lot About You

As part of the Consumer Monetization Platform Engineering team, you will be working on data engineering pipelines and next-generation Machine Learning- and AI-based data infrastructure, supporting new functionalities on existing platforms, and mining data for analytics insights and product features.

Our Big Data footprints are among the largest few in the world, at double-digit petabyte scale. Developing this infrastructure presents many technical challenges in the areas of efficient query processing, large-scale stream processing, machine learning and modeling, as well as satisfying complex business rules.

If you are someone who is  enthusiastic about harnessing data at insane scale, enjoys working with new technologies, setting up petabyte data infrastructures, and implementing new machine learning solutions and metrics systems, we want to hear from you!

Your Day

• Improve our existing data infrastructures for machine learning and deep learning using your core expertise

• Design and build unified, production-grade streaming and batch data pipelines that achieve full event coverage with near-real-time latency

• Develop schema optimization and compression strategies for efficient large-scale data ingestion and storage

• Build the data foundation for ML training pipelines—including feature engineering, real-time feature serving, and batch feature computation—that powers yield optimization and predictive analytics

• Work with other engineers to implement algorithms and systems in an efficient way

• Take end-to-end ownership of Machine Learning-based distributed data systems—from data pipelines and training, to real-time prediction engines

• Develop complex queries, very large volume data pipelines, and analytics applications

• Develop complex queries and software programs to solve analytics and data mining problems

• Build data quality monitoring systems, automated anomaly detection, and reconciliation processes for production-grade revenue operations

• Interact with data analysts, data scientists, product managers, and software engineers to understand business problems and technical requirements to deliver data solutions

• Prototype new metrics or data systems

• Lead data investigations to troubleshoot data issues that arise along the data pipelines

• Maintenance and improvement of released systems

• Engineering consulting on large and complex warehouse data
   

Qualifications

• BS with 7+ years of relevant Industry experience/M.S. in Computer Science with 5+ years of relevant Industry experience. Computer Science graduate ideally with specialization in Data Engineering or Machine Learning

• Strong fundamentals: algorithms, distributed computing, data structure, database

• Fluency with at least one of: Go/Java/Python/C++/Scala/SQL

• 5+ years of industry experience on very large scale analytics or ML systems development

• 2+ years of experience with Google Cloud Platform (BiqQuery, Dataproc, Composer, Dataflow, BigTable, etc.)

• 2+ years of experience in Hadoop technologies (Map/Reduce, Pig, Hive, HBase, Spark, Kafka, Oozie, etc.