Staff Software Engineer - Social Integrations

Staff Software Engineer  - Software Engineering Department

Location: Soho, Manhattan, NYC

About the Company 

DoubleVerify  (“DV”), (NYSE: DV) is a big data and analytics company. We measure and analyze tens of billions of ads every day for the biggest brands in the world like Apple, Nike, AT&T, Disney, Vodafone, and most of the Fortune 500 companies. If you ever saw an Ad online via Web, Mobile or CTV device then there are big chances that it was analyzed and measured by us.

We operate at a massive scale, our backend handles over 100B+ events per day, we analyze and process those events in real-time while making decisions on the environment where the ad is running and all the user interactions during the Ad display lifecycle. We verify that all Ads are Fraud Free, Brand Safe, in the right Geo and highly likely to be viewed and engaged, all that in less than a fraction of second.

We are global, we have R&D centers in Finland, Tel Aviv, New York, Belgium and San Diego. We work in a fast-paced environment and have a lot of challenges to solve. If you like to solve big data challenges and want to help us build a better industry than your place is with us.

Learn more at www.doubleverify.com

Position Overview 

As a Staff Software Engineer, you own new initiatives, designs and build world-class platforms in order to measure and optimize ad performance. You ensure industry-leading scalability and reliability of mission-critical systems processing billions of real-time transactions a day. You apply state of the art technologies, frameworks, and strategies to address complex challenges with Big-Data processing and analytics.

What will you do?

• Architect, design and build application pipelines handling tens of TBs/Day, serving thousands of clients and supports advanced analytic workloads
• Mentor  a great team of motivated engineers by reviewing, understanding, and providing actionable feedback on code, architecture designs, and infrastructure deployments created and maintained by other engineers
• Explore the technological landscape for new ways of producing, processing, and analyzing data in order to gain insights into both our users and our product features
• Design, develop, and test data-driven products, features, and APIs that scale
• Continuously improve the quality of deliverables and SDLC processes
• Operate production environments, investigate issues, assess their impact, and come up with feasible solutions.
• Understand business needs and work with product owners to establish priorities 
• Bridge the gap between Business / Product requirements and technical details
• Work in multi-functional agile teams with end-to-end responsibility for product development and delivery

Who you are?:

• Lead by example - design, develop and deliver quality solutions.
• Love what you do and are passionate about crafting clean code and have a steady foundation with 8+ years of programming experience in coding, object-oriented design and/or functional programming
• Deep understanding of distributed system technologies, standards, protocols, and have 3+ years of experience working in distributed systems like Hadoop, Big Query, Spark, Kafka Eco System ( Kafka Connect, Kafka Streams), and building data pipelines at scale.
• Hands-on experience building low latency, high-throughput APIs, and are comfortable using external APIs from platforms.
• Excellent SQL query writing abilities and data understanding
• Care about agile software processes, data-driven development, reliability, and responsible experimentation 
• Genuine desire to automate decision making, processes, and workflows
• Experience working with dependency management tools such as Luigi/Airflow
• Experience with DevOps domain - working with build servers, docker and containers clusters (kubernetes)
• Experience in Mentoring and growing a diverse team of talented data engineers
• B.S./M.S. in Computer Science or a related field
• Excellent communication skills and a team player
  

Extra credits for having experience with:

• Columnar data stores
• Google BigQuery
• Spark Streaming or other live stream processing technology
• Cloud environment, Google Cloud Platform 
• Container technologies - Docker / Kubernetes
• Ad serving technologies and standards 
• Akka