Big Data Engineer

at  Zattoo

YOUR FUTURE, ON DEMAND

The ideal blend of stability and flexibility. A genuinely human employer that cares for people and the planet. True autonomy to shape what comes next, for us and you. This is the perfect platform to take your career where you want.
Back in 2005, we pioneered Europe’s first TV streaming service. Today, we’re the world’s first certified climate neutral TV streaming provider. 3 million users across three countries. Over 230 colleagues of 47 nationalities. We’re the grown-up start-up, helping to shape a better future since day one. That hasn’t changed, even if the world has. We’re friendly, international, inclusive – and our people say we’re reliable and transparent, too. It’s why they trust us and believe in what we do.

THE ROLE

Data is a core advantage of OTT/Unicast TV over traditional broadcast. As a platform operator we know exactly what content our users watch, how popular a show is and how many seconds of each and every ad campaign is viewed. With roughly 3 million active users every month the data we collect from them allows for efficient and precise business processes and data based decision making.
At Zattoo, we already leverage a lot of our data (we process 6TB daily!) and still want to do more. We want to build day to day business decisions more on hard facts and less on gut feeling. Therefore we are searching for an experienced Big Data Engineer to join our motivated and growing data team. You will be shaping the big data architecture in this company and building data components that change the way data is leveraged in this company!

WHAT YOU’LL DO

• Collaborate with the entire data team and core engineering to enable data based decision making and data based products
• Build, maintain, and tune highly scalable event streaming, and batch pipelines
• Manage and evolve our cloud based and on premises Data Warehouse (Big Query, Vertica, Clickhouse) which acts as the unique source of all relevant data, and ingests high volume near-real time data from various sources
• Be the in house expert on systems, processes and software to best track, store, process and access data
• Design and evolve our data processing pipeline to feed analytical needs and data products ranging from self service analytics to machine learning modules
• Set high standards for quality, stability and robustness of the data and processes