The RoleThe Staff Software Engineer will join and lead DV's Programmatic software development team and will use industry standards and latest technologies to enhance our programmatic and platform products. 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 you'll do- Architect, design, and build big data processing platforms handling tens of TBs/Day, serve thousands of clients, and support advanced analytic workloads
- Set technical direction and influence across teams to align data platform investments with broader engineering and product strategy
- Provide meaningful and relevant feedback to junior developers and stay up-to-date with system changes
- Drive adoption of AI coding tools and AI-assisted workflows across the team to improve day-to-day developer productivity and SDLC efficiency
- Explore the technological landscape for new ways of producing, processing, and analyzing data 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 develop 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- 10+ years of programming experience in software engineering, 5+ years of experience in data engineering
- Strong proficiency in both Java and Python, with the ability to operate fluently in either language across production codebases
- Deep understanding of big data technologies, standards, and protocols, and 5+ years of experience working with big data platforms like Snowflake, BigQuery, Databricks, Airflow, dbt, Spark, Pub/Sub ecosystem (Kafka Connect, Kafka Streams, or Kinesis), and building data pipelines at scale
- Excellent knowledge in SQL query and data modeling
- Familiar with AI coding tools and best practices in leveraging AI in SDLC
- Experience with Google Cloud Platform
- Experience with DevOps domain - working with build servers, Docker, and container clusters (Kubernetes)
- Full-stack development experience - building backend API services (e.g., REST/gRPC) and working with a modern frontend framework (e.g., React, Vue, or Angular)
- Experience with agile software processes, data-driven development, reliability, and responsible experimentation
- 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
- Lead by example - design, develop, and deliver quality solutions
- Experience with ad-serving technologies and standards is a plus
The successful candidate's starting salary will be determined based on a number of non-discriminating factors, including qualifications for the role, level, skills, experience, location, and balancing internal equity relative to peers at DV.
The estimated salary range for this role based on the qualifications set forth in the job description is between $131,000 - $260,000 This role will also be eligible for bonus/commission (as applicable), equity, and benefits.
The range above is for the expectations as laid out in the job description; however, we are often open to a wide variety of profiles, and recognize that the person we hire may be more or less experienced than this job description as posted.
Not-so-fun fact: Research shows that while men apply to jobs when they meet an average of 60% of job criteria, women and other marginalized groups tend to only apply when they check every box. So if you think you have what it takes but you're not sure that you check every box, apply anyway!
