Junior Data Engineer (m/f/d)

Job content

Artefact, a global AI and data consulting company with skyrocketing growth, is looking for a talented, energetic junior data engineer for its nascent German tech team.Will it be you?

Who We Are

Artefact isa new-generation AI consulting company.For an early-career professional like you,we are the best school to learn about data science and MLin an applied business context:

• We are growing quickly... We have been growing enormously fast over the past few years, and want to grow by an additional factor of 4 over the next 4 years. If you join us, you will be an early member of an expanding team.
• …while already having a global scale. We are about 1,200 now, with a tech team of over 300, scattered across 20 offices on every continent.
• We have a proven track record of making people grow fast. Artefact alumni have created startups, led technical teams at companies big and small, been hired by Google and Amazon, etc.
  

As a Junior Data Engineer

WHAT YOU WILL DO

• You will help set up, implement, and maintain data pipelines. Most of our missions revolve around data pipelines, although we can intervene at different stages of the life cycle, from creating a data platform from scratch, transitioning to new data architectures, to auditing the security of an existing setup, etc.
• You will gain a wide range of data engineering experience. You will be expected to work on a few missions a year (1-3), which will expose you to different industries, use cases, and technologies. Even within a mission, your day-to-day tasks might vary a lot!
• You will see the real-world impact of your work. Unlike other companies that specialize in fancy vaporware, we specialize in building solutions that can be used for years and actually make a difference for our clients. This also means that you will get experience interacting with clients and non-technical people.
• You will work with cutting-edge tools. Our stack varies from client to client, but is generally quite modern — GCP with Terraform, DBT, and Vertex AI, to name a recent example. Python is generally the programming language we use, though.
  

Must-have Requirements

We will primarily judge your application on the following criteria:

• You are proficient in one programming language (preferably Python, but it can be C++, Java, etc.). If that language is not Python, we have to be confident you can pick it up easily.
• Beyond your programming skills, you have a real data culture: you know your way around ETL workflows and database concepts, you can perform SQL queries, you know how to manually process numbers and strings…
• You have excellent problem-solving skills, and you can learn fast.
• You can be operational in a team of programmers: you know how to use Git, you can write unit and integration tests, you can clearly explain your work to your colleagues, you know how to look for external resources and ask for help, etc.
  

We strongly prefer if you’re a German resident, although we’ll consider great candidates within the EU.

Nice-to-have Requirements

We’re not expecting anyone to meet all of these requirements, but you should at least meet a couple of these:

• You have a data science background in addition to your software engineering skills, and are able to be a sort of hybrid profile between data scientist and data engineer.
• You have experience working on production systems or with client data.
• You’ve previously worked in Agile/Scrum environments, and you know your way around tools like Jira.
• You have very advanced SQL skills, and are able to write queries that are both powerful and efficient.
• You already have experience with building data pipelines for ML/AI projects, using technologies such as Airflow, Kedro, Spark, etc.
• You have significant knowledge of database systems, and know what are the best setups for specific data use cases.
• You’re a budding MLOps expert, and know how to manage and monitor machine learning models in production.
• You have significant experience with cloud environments (AWS, Azure, GCP). Bonus point if you’ve worked with the data engineering components of these cloud environments (Dataflow / Vertex AI / Dataproc, Sagemaker, HDInsight, Databricks, etc.)
• You know your way around networking and security concepts.
  

OUR INTERVIEW PROCESS

The typical interview process is pretty short, and is structured as thus:

• HR Screening (30 minutes): A phone screen with a recruiter to make sure expectations are aligned.
• Fit Interview (30 minutes): A short call with a consulting manager to get to know you and explore how Artefact and you might fit together.
• Technical Interview (1 hour): An interview with our technical manager divided into 3 parts. (1) Behavioral questions (e.g. what is your experience? what type of job do you want to have?); (2) Data engineering scenarios to check your general ability to engage with such problems; (3) A live coding test that mirrors a task you could encounter in your day-to-day life. (We don’t do LeetCode here.)
• Take Home (flexible): We’ll give you a real-world use case, with code in a repository and a business problem. You’ll have as much time as you want to complete the assignment (we typically give 1 week, although we observe that it takes about a few hours to complete). When you’re done, we’ll schedule a slot for you to review your results and your code.
  

If doing a take home is not practical for you, we can alternatively schedule a live programming session. We sometimes skip the take home for exceptional candidates.

OUR CULTURE

• We are a consulting company, which is great if you want to get more exposure to business and work alongside people with very diverse skill sets. But Artefact might not be for you if you want to work on the same project for years, or if you want to interact only with fellow engineers.
• Our team is remote-first, and we don’t care where you work. We would like to see you in Hamburg a few times a year, though. (Don’t hesitate to ask us about our remote policy during the interview process.)
• We are uncompromising on work-life balance (in a good way). Nobody at Artefact is expected to be on-call at night, and we push back against unreasonable client requests.
  

Our Benefits

• Very competitive compensation package, with twice-a-year bonuses.
• Flexible equipment options.
• We have some budget for home office equipment (such as an external monitor).
• 6 weeks PTO + 4 weeks of “workation” per year.
• Financial support for training and studies.
• Subsidies for mental health apps and bike leasing.
• Corporate pension plan.
• We have an excellent espresso machine in Hamburg, fwiw.
  

This list is specific to Germany, and might change slightly otherwise.

If you have any questions, feel free to message us at leopold.mebazaa+jobs@artefact.com or michael.voelske+jobs@artefact.com.

We encourage candidates from all backgrounds and are welcoming you regardless of gender, race, or LGBT+ background.