Data Infrastructure Engineer
Zenreach was created to solve one of the most important problems in the modern economy—the majority of our time is being spent online, yet over 93% of purchasing still happens offline — and there is no link between the two systems. Brick-and-mortar merchants are working decades behind their online counterparts without essential data and tools. We created Zenreach to give them the same level of technology and transparency that anyone operating online has come to expect.
Zenreach is looking for an experienced data engineer to join our team! Our product team is a small, tightly-knit group working on building the smartest e-mail outreach platform ever. What makes us different? What Google did with cost-per-click for online marketing, we're doing for the offline world. If you want to build something that's never been done before and help thousands of local businesses in the process, please join us!
You're excited to:
- Work with large datasets and build systems to handle fast and correct streaming computations
- Build large scalable, fault-tolerant, distributed systems
- Build libraries and frameworks to help other engineering teams compute data fast and correctly
- Build systems to enable new, exciting calculations using our data
- Grow into a leader on a fast-growing, key engineering team
- On scalable, distributed systems
- With realtime streaming technologies (such as Kafka and/or Kinesis)
- With Scala (or have strong experience with other JVM languages and a willingness to learn)
- On large distributed data-oriented systems (Hadoop or others)
Technologies we use:
- Kafka Streams library
Perks / Benefits
- Flexible hours of work plus the option to work from home
- Flexible vacation plan
- Enhanced paternity and maternity leaves
- Bright and open workspace which includes a ping-pong table, fully stocked kitchen with healthy (and unhealthy) snacks
- Catered lunches on Thursdays
- Organized volunteer events to give back to our community and plenty of off-sites and happy hours to relax and unwind.