Senior Data Engineer
68k - 92k USD
Hybrid
Full Time
#Data Engineering
#Cloud
#Machine Learning
#Apache Spark
#Databricks
#SQL
#NoSQL
#Linux
At DATAPAO, data ignites passion, community fuels collaboration, and growth knows no bounds. We are a leading Data Engineering and AI consulting company backed by Databricks and recognized for our unmatched delivery standards and rapid growth. We have been named Databricks EMEA Emerging Business Partner of the Year (2024), achieved the Golden Tier status in the Databricks Partner Program, and made two consecutive appearances on the Financial Times FT1000 list.
We are currently looking for a well-versed (Senior) Data Engineer to work with our EMEA and US customers and help them solve their data engineering, ML and/or ML Ops, and cloud migration puzzles.
As a Data Engineer, you are expected to deliver (across industries) on some of our most complex projects - individually or by leading small delivery teams. Although we work for the biggest multinational companies where years-long behemoth projects are the norm, our projects are fast-paced, typically 2 to 4 months long. The majority are delivered using Apache Spark/Databricks on AWS/Azure and require you to directly manage the customer relationship, alone or along with a Project Manager. Additionally, at this seniority level, we expect you to compound your impact across the team and the organization - by mentoring more junior engineers, evaluating the quality of their work, and contributing to hiring best-in-class data engineers.
What does it take to fit the bill?
- Consultant mindset & passion for customer experience - you prioritize your work with the customer in mind and you seek to advise (rather than purely execute) your customers on the best-in-class technical solutions;
- Excellent communication & presentation skills - you can adjust your communication style, and articulate complex, technical concepts to all types of audiences;
- Solid software engineering foundations - you are a stack-agnostic senior software engineer, have significant experience working on Unix/Linux, and a strong understanding of how Distributed Systems work. Additionally, you are familiar with (and keen to follow) best-in-class software engineering principles;
- Data & Cloud are part of your engineering journey - you played a role in teams that designed and implemented data-intensive applications and you have strong SQL & NoSQL hands-on experience. Exposure to Real-Time Data Processing Systems, Apache Spark, and/or the Big Data ecosystem is an advantage;
- Mentoring skills & strong predisposition to knowledge-sharing - are things that excite you. We consider ourselves a learning organization and believe that these are meaningful tools for one to compound his/her impact across the team and the organization. Thus technical mentoring and/or people management hands-on experience is a big plus;
- You thrive when having to solve problems & take ownership - you solve problems on your own and advise (or coordinate) others on how to do the same. Moreover, you love stepping up as a technical lead or identifying organizational gaps and filling them in - being an organizational process or documentation gap, a customer communication miss-match, or a resource allocation deficiency;
-
You are fluent in English and willing to travel (mainly in the EU and normally within a short business trip setup) up to 15% of your time.
What do we offer?
-
Educational benefits: There’s no shortage of learning opportunities at DATAPAO, meaning that you'll get access to Databricks' public and internal courses to learn all the tricks of Distributed Data Processing, MLOps, Apache Spark, Databricks, and Cloud Migration from the best. Additionally, we'll pay for various data & cloud certifications. You'll also get dedicated time for learning during work hours and access to our internal library.
-
Flexible PTO and Working Hours: We’re flexible about your working routine and how many days you take off if it does not conflict with customer success, company goals, and the work you do.
-
Flexible Office: It is up to you which days you spend in the office. However, as a strong community is one of DATAPAO's value propositions, we’d expect you to spend one day per week in the office on average.
-
30 Calendar Days of Paternity Leave (if applicable): We think it’s essential for both parents to be there when it matters the most.
-
Private Medical Insurance: We provide a private medical package via Generali.
-
Employee Assistance Program (EAP): Through EAP, we offer our employees access to psychological, financial, and legal consulting services via phone or in person.
-
Top-notch working equipment: Working comfortably means working well. Therefore, you will get a MacBook, a Herman Miller office chair, standing desks in the office, and whatever else is needed to give your best.
-
The chance to make an impact in a high-transparency culture: Open feedback and a no-politics environment are things we value a lot at DATAPAO. Additionally, you'll get the chance to shape the future of a rapidly growing tech company, to work with cutting-edge technologies, and to help some of the biggest and most innovative companies in the world sort out their data puzzles.
-
A cozy and modern office in the heart of Budapest: Located in a vibrant, central part of the city (Opera/Oktogon), it's designed to foster focus, creativity, and team connection. You'll find open spaces for group work, quiet corners for deep thinking, and plenty of natural light. It’s well-stocked with snacks, drinks, coffee, and beverages. Optional Friday evening beers, movie, and wine-tasting nights with the team are also on us.
The gross salary for this position ranges from gr. 1.200.000 - 1.700.000 HUF/month for a Medior and from gr. 1.700.000 - 2.300.000 HUF/month for a Senior role, depending on your assessed seniority level during the selection process.
Want to know more about us?
DATAPAO is a Data Engineering and AI company that covers the entire data transformation from architecture to implementation. Beyond delivering solutions, we also provide data and AI training and enablement.
We are backed by Databricks - the creators of Apache Spark, and act as a delivery partner and training provider for them in Europe. Additionally, we are Microsoft Gold Partners in delivering cloud migration and data architecture on Azure. Our delivery partnerships enable us to work in a wide range of industries and with some of the most prominent global companies, such as Norsk-Hydro, Richter, Bayer, Schufa, GetYourGuide, TechnoAlpin, and Logically, to name just a few.
As a training provider, we deliver onsite and online courses globally for Databricks and on our own. We have been teaching professionals at Apple, Amazon, Uber, Microsoft, T-Mobile, GE, Ericsson, and many more to improve their impact with data.
For even more insights, check the links below:
-
Designing and Implementing a Real-time Data Lake with Dynamically Changing Schema (EN) by Máté Gulyás (2021, Spark AI Summit)
-
Productionising Machine Learning models (EN) by Máté Gulyás (2023, Mndwrk Event)
-
"Ha a data governance jól működik, az olyan, mint egy láthatatlan szupererő” (HU) by Máté Gulyás (2023, Com-Forth Zóna Podcast)
You can also follow us on LinkedIn for all the good stuff or just hit our recruitment team at [email protected]
We’re firm believers in scaling up a team without judgment or prejudice. What we really care about is working with the best people out there, no matter their background. And you should also not worry if you don't tick every box in the requirements. If you’re passionate about data and learning new things, you’ll fit right in, and we'd love to hear back from you.
When we hear back from you, we'd like you to know that we are committed to your privacy and keeping your data safe. We do not share your data with any third parties (except the ones we use to run our recruitment process) and keep your application for two years unless you ask us otherwise. We use your data solely for recruitment purposes, such as letting you know about new career opportunities at DATAPAO and/or managing your application. But if you want to know more about how we store and manage your data, check our privacy policy.
