The role of Data Engineer can be considered as one of the most sought after positions. What does it mean to be a data engineer and how does it differ from being a software engineer or being a data scientist? Fokko Driesprong, data engineer at GoDataDriven, took the time to give us a glimpse of his daily life.
As soon as I have arrived at the client’s office and have brewed myself a cup of coffee, the first thing I do is open Slack to see if there are any notifications from Apache Airflow. Usually, these are low-priority notifications, as all urgent notifications are always taken care of upon the first notification. If it’s an easy fix, I’ll get on it right away. If not, I’ll schedule it for later or delegate the issue to a team member.
At 9.30 am, the team gathers for the daily stand-up. This is where we discuss yesterday’s progression, today’s schedule, and any issues we’re having.
On Thursdays every other week we discuss the sprint schedule to determine what we’ll be working on.
Picking The Best Technology for Any Project
My job requires me to work on very diverse projects. The thing that I enjoy most is employing the latest technology for every client, preferably open-source.
For instance, right now I’m working on containerising event stream collectors, to run them on a Kubernetes cluster. It’s always a joy to work with our in-house developed open-source clickstream collector, Divolte, but I don’t mind using other collectors too.
For another client, I recently implemented a Druid platform. There, I had the opportunity to work with Deck.gl, a Superset integration to visualise data in 3D on a map. The cool thing is that Superset was developed by AirBnB as a data exploration tool and that this specific integration was developed by Uber.
Business-Critical Systems with Terabytes of Data
More and more of my work takes place in the cloud, for example setting up date infrastructure on AWS or GCP. When configuring buckets, I make sure that sensitive information – such as personal details – is properly protected using service accounts.
Because I often work on business-critical systems with terabytes of data flowing through them, it’s important for me to be well versed in the underlying technology. If the systems crash, end users no longer get recommendations or the managers’ figures run out of date. When that happens, people get nervous. Naturally, that’s something I always try to prevent.
New tools are made available every day, so needless to say, I’m constantly working to keep my knowledge up-to-date. I read a lot of blogs and I keep up with interesting projects on Github. At GoDataDriven, continuous knowledge sharing is ensured by for example our biweekly knowledge exchanges on Tuesdays and the GoDataDriven Fridays. During this day, everyone gets time to work on their own projects. Me and my colleagues receive a generous training budget, which I use to attend conferences such as Berlin Buzzwords, Spark Summit or Strata Hadoop. As colleagues, we also regularly consult with each other to discuss solutions to challenging issues.
I think it’s important for any organization to develop the ability to work with the system or product we developed independently. That’s why I don’t mind spending time with the client behind the MacBook to give them instructions.
Interested in working alongside Fokko?
You are passionate about helping organizations drive their success with Data & AI. You feel comfortable operating at the sweet spot between Leadership, Business, and Tech. And, after co-creating a vision and strategy on Data & AI, you’re not afraid to kick-start and drive the execution with a top-notch team that will turn your ideas into reality.
Your passion is data and analytics. You want to create value at our clients by uncovering, organizing, and making sense of data. You understand that it is important to build robust solutions. You feel comfortable to operate in the sweet spot between business and engineering.
You love to help organizations become successful with Data & AI. You have been a practitioner as analyst or scientist. You feel comfortable to approach stakeholders and help them to uncover the needs of their business. And you are not afraid to take ownership and make sure the right solution goes into production.
You are a engineer with a pragmatic attitude. You feel the weight of responsibility that comes with taking systems into production. You easily switch between scripting and structured programming in typed languages. You understand cloud, provisioning and automation. And you know how to build robust systems.
You are passionate about sharing your knowledge and helping others in their development and success stories and feel comfortable explaining difficult subjects on various levels and are adept at creating new learning and development offerings on Data & AI. You are fluent in Python and the most used data science libraries such as Pandas and scikit-learn. Clean code comes naturally to you and you understand why that is important for the next generation of data science products.
We are looking for senior data scientists who feel at home at the intersection between science, mathematics, machine learning, business, and coaching. You have experience in building value from data through ML and software.
You understand ML. You understand that scale is not trivial. You like to code. You are comfortable to be a bridge between data scientists and data engineers to build production-ready, scalable applications driven by data and AI.