Senior Data Engineer, Scala
New York City, NY
Boston, MA
At Magnite, we cultivate an environment of continuous growth and collaboration. Our work impacts what millions of people read, watch, and buy, and we’re looking for people to help us tackle that responsibility with creativity and focus. Magnite (NASDAQ: MGNI) is the world’s largest independent sell-side advertising platform. Publishers use our technology to monetize their content across all screens and formats including CTV / streaming, online video, display, and audio. Our tech fuels billions of transactions per day!
Magnite conducts 400+ billion ad request auctions daily carrying $450+ million of revenue annually. To stand out among competitors, Magnite strategically focuses on being the most efficient, highest scale independent exchange.
About this team:
The Streaming Organization’s Data Engineering team owns the applications and infrastructure that make up the Streaming Org’s data pipeline, handling ~40 billion events per day at an average of 400-500 thousand per second. This data underpins the Streaming business - including client reporting, internal data science, account managers, and product + business teams - and as such we need to build systems that remain scalable and efficient at this volume of data while also ensuring data consistency and reliability. We value communication, discussion, and sharing of ideas to come to the best technical solutions to our large-scale data challenges. We are looking for people who want to get things done and value open collaboration (including constructive feedback when brainstorming). Our end-to-end ownership of the data world includes both typical data-engineering type problems (think Spark pipelines, ETL processing, etc) and more general software-engineering tech as well (think Java applications, API design, etc).

In this role you will:

• Get to work on handling internet-scale data problems
• Help architect and build systems to process our data volume to empower all consumers
• Join in on full end-to-end ownership of the team’s data pipeline and related systems for data delivery
• Be a part of and promote our culture of collaboration and mentorship

Typical challenges we face in this role include:

• Highly-scalable infrastructure: Our traffic has patterns with peak- and off-peak times and seasonal shifts, and our data infrastructure needs to be able to respond accordingly
• Cost optimization: Improving profit margins by lowering the infrastructure cost basis through building efficient systems
• Technical architecture considerations given various SLAs for data delivery

We’re looking for someone:

• With 4+ years of software development experience with a BS/MS Computer Science or equivalent work experience
• Who wants to take ownership. We are responsible for the entire software development lifecycle, from requirements gathering to production support
• To engage in critical and creative thinking. We expect engineers to present and discuss tradeoffs to solve the problems we face
• With either existing experience designing and building systems that work with large-scale data volumes and data ingestion systems at scale in a cloud-first setting, OR established technical excellence with a desire to learn and crush the data engineering world

Our current tech stack:

• Java or Scala for core application development
• Spark (batch + streaming) for data pipeline development, currently based on Databricks
• Terraform, Docker, Jenkins for CI/CD / infra / application deployment
• Airflow for job orchestration
• AWS-based cloud infrastructure including RDS, EC2, S3, Kinesis, ECS

Comprehensive Perks and Benefits:

• Comprehensive Healthcare Coverage for You and Your Family from Day One
• Generous Time Off
• Holiday Breaks, Summer Fridays and Quarterly Wellness Days
• Equity and Employee Stock Purchase Plan
• Family-Focused Benefits and Parental Leave
• 401k Retirement Savings Plan with Employer Match
• Disability and Life Insurance
• Cell Phone Subsidy
• Fitness and Wellness Reimbursement

Company Culture:

• Community Service and Volunteer Events
• Company-Matched Charitable Contributions
• Wellness Coach and Mental Health Support
• Career Development Initiatives and a Career Growth Framework
• Culture and Inclusion Programs
• Bonusly Peer-to-Peer Recognition Program

About Us
The world’s leading agencies and brands trust our platform to access brand-safe, high-quality ad inventory and execute billions of advertising transactions each month. Anchored in bustling New York City, sunny Los Angeles, mile high Denver, historic London, and down under in Sydney, Magnite has offices across North America, EMEA, LATAM, and APAC.
The base salary range for this position, across all United States geographies, is $150,000 - $170,000 per year. The upper portion of the salary range is typically reserved for existing employees who demonstrate strong performance over time.
Magnite is an Equal Opportunity Employer and does not discriminate against applicants due to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation or any other federal, state or local protected class.
Our Commitment: We aim to incorporate a wide range of voices into our Magnite culture, cultivating an environment where employees feel welcomed, cared for, and encouraged to freely share ideas. We are committed to employee growth, collaboration, inclusion, and innovation. We invest in Magnite’s local communities. We seek talent from all backgrounds to champion corporate values of seeing the big picture and being catalysts of change.
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Recruiting Agency Notice
Magnite does not accept agency resumes and is not responsible for any fees related to unsolicited resumes

In this role you will:

• Get to work on handling internet-scale data problems
• Help architect and build systems to process our data volume to empower all consumers
• Join in on full end-to-end ownership of the team’s data pipeline and related systems for data delivery
• Be a part of and promote our culture of collaboration and mentorshi

Typical challenges we face in this role include:

• Highly-scalable infrastructure: Our traffic has patterns with peak- and off-peak times and seasonal shifts, and our data infrastructure needs to be able to respond accordingly
• Cost optimization: Improving profit margins by lowering the infrastructure cost basis through building efficient systems
• Technical architecture considerations given various SLAs for data deliver