About Us

MediaMath is the leading technology pioneer on a mission to make advertising better. We deliver outstanding results through powerful ad tech, partnership and a curiosity for what’s next. We help more than 3,500 advertisers solve complex marketing problems so they can deepen their customer relationships across screens and around the world.

Key Responsibilities

MediaMath’s Analytics Engineering team is currently seeking a Data Engineer with the knowledge, passion, and capability to build and work with complex datasets that are used by Analytics to discover and deliver insights that drive value for our clients. The Analytics team fulfils customers’ advanced analytics and reporting needs through custom reports and analyses, advanced statistical applications, predictive modelling and interactive web dashboards to help clients effectively manage campaigns and optimize performance. As the Data Engineer on the Analytics Engineering team within the Analytics team, you will support these initiatives through building, maintaining, and optimizing data infrastructure

You will:

• Become an expert in MediaMath data flows and the Analytics data infrastructure.
• Build, maintain, and own scalable data pipelines to support client data integration.
• Become a team SME in data munging and automated ETL processes.
• Work with Analysts to understand and leverage big data to solve client problems and needs.
• Ensure that data pipelines/systems adhere to team and company standards, and raise the bar on the standards when possible.
• Be a team player, and bring the team and company forward by solving team and company priorities.

You are:

• Experienced in writing readable, re-usable code SQL and Python (our entire team uses Jupyter Notebook and Pandas!)
• Experienced with distributed system technologies, Hadoop, HiveQL, and Spark SQL/PySpark
• Experienced in implementing data pipeline health monitoring, alerting
• Experienced with data infrastructure troubleshooting and working with system logs
• Experienced developing data flow schematics/blueprints
• Advocate for automation and building efficient, scalable solutions
• Self-driven, with a hunger to learn and spread knowledge by teaching others
• Excellent communication skills – ability to synthesize and communicate technical concepts, limitations, and requirements to client-facing teams and stakeholders

You have:

• Bachelor’s Degree or higher, preferably with a concentration in a computational field such as Computer Science, Mathematics, Statistics, Physics, Engineering;
• 3 - 5 years of experience in building, troubleshooting, and optimizing production ETL pipelines - ideally held a Data Engineer position previously
• Experience with data modelling, data integration, and working with disparate data sources, including APIs and relational databases
• Experience partnering with client-facing teams to understand client needs and translate them to technical requirements

Nice-to-have’s:

• Experience with cloud computing technology, preferably AWS (EC2, S3, RDS, Lambda)
• Experience working with REST APIs, web services, object-oriented technologies like Java, C++
• Public GitHub repos or notebooks that illustrate the way you think about data
• Exposure to ad-tech, digital marketing, or e-commerce industries

Why We Work at MediaMath

We are restless innovators, smart, passionate and kind. At the heart of our culture are three values that provide a framework for how we approach our work and the world: Win Together, Obsess Over Growth, and Do Good, Better. These values inform how we energize one another and engage with our clients. They get us amped to come to work.

Founded in 2007 as a pioneer in "programmatic" advertising, MediaMath is recognized as a Leader in the Gartner 2020 Magic Quadrant for Ad Tech and has won Best Account Support by a Technology Company for two years in a row in the AdExchanger Awards.

MediaMath is committed to equal employment opportunity. It is a fundamental principle at MediaMath not to discriminate against employees or applicants for employment on any legally-recognized basis including, but not limited to: age, race, creed, color, religion, national origin, sexual orientation, sex, disability, predisposing genetic characteristics, genetic information, military or veteran status, marital status, gender identity/transgender status, pregnancy, childbirth or related  medical condition, and other protected characteristic as established by law.