Job description

We are looking for a Data Engineer to join our Data Team. You will be responsible for developing, implementing, and monitoring the Data Pipelines of several games of the group. You will work inside the Data Team (1 Data Engineer, 2 Analytics Engineers, 4 Data Analysts, 1 Data scientist) and you will report to the Head of Growth and Data.

We use a modern data stack that is primarily composed of Google BigQuery, dbt, Airbyte, Prefect, Deepnote and Looker. The Data Engineering activities focus on GCP, Airbyte, Prefect but also includes Prometheus, Thanos, Graphana tools and Kubernetes nodes management.

Team description

The Data team at 52 entertainment is full of talents working on Business & Financial, Product and Marketing KPIs. It is a cross-functional team that connects with all business units (US, Europe, Asia).

The Data team is fully remote (but all the team is currently based in Europe). We are using top notch communication & project management tools (Slack/Jira/Confluence) and a fantastic stack of technical tools (Airbyte, Prefect, Google Big Query, dbt, Looker, …) .
We talk to each other on a daily basis and organize frequent virtual coffees ☕️.

Some are geeks, some are not, apply as you are, we’re a diversity-friendly team 🧕 👧🏽 🥷 👨🏿 👩 🦾.

Stack

Data: Airbyte, Prefect, Google BigQuery, dbt, Github, VSCode, Deepnote & Looker
Project Management: Slack, Google Drive, Confluence, Jira

Missions

• Create, monitor, and optimize Data Pipelines for existing Games and third-party sources.

• Manage relations with B.U. Developers and be proactive to prevent pipeline deprecation because of products evolution.

• Ingest third-party data and setup data consumption endpoints.

• Ensuring best practices for data integrity and performances.

• Investigate new initiatives like Data Cataloging, Data Discovery, ML Ops

• Provide our Data Scientists with Big Data tools that will allow them to process our data more easily (prediction, machine learning, …).

We’re excited about you because…

• You’ve been hesitating between Dev Ops and Data Engineering for a while, but realized that the later was much more fun
• While you already have some experience in this role, you are passionate to learn even more and want to grow as an expert in a friendly team, while being coached by a senior Data Engineer.
• You can easily discuss technical concepts with other Dev Ops to help other teams create systems you will need to connect your pipelines to.
• You like to learn new concepts and tools and are not afraid of getting your hands dirty.

Benefits

• Work in a start-up with exceptional growth
• Highly interesting work environment with flat hierarchies, fast pace and fun
• You’ll have a real impact on people’s lives! If you have the potential, we will do everything to help you to achieve the highest level of personal and professional development.
• Ultimate flexibility. we try to have team overlap every day, but outside that work whenever and wherever you work best.
• Extreme autonomy. No micro-managing here. After onboarding, you’ll be given high-level direction and then left to solve it the way you feel is best.
• Amazingly friendly Data team.

Your Profile

• Between 1.5 and 4 years of experience of experience either in Data Engineering, Big Data or DevOps

• Familiar with modern data stacks and principles (cloud-based platforms/data-lakes and managed services)

• Skilled in SQL and Python

• Experienced in working in interdisciplinary teams and in multi-cultural team environments

• Strong communication skills and facilitation abilities

• Priorities management & time management skills

• Highly open minded

• Diplomacy, pedagogy and humility

• Fluent English.

• Collecting applications until April 7th 2023

• First interviews from March 27th 2023 onward.

• Our hiring process is sequential : we know job seeking is a stressful time of life, and we’ll make sure things are transparent from our side. If you don’t pass step 2, we won’t waste your time on step3.

Interview steps

• Step 1 Visio-call - Preliminary interview where the scope of mission, our company, your aspirations, and salary compensation are discussed to see if we agree on the important things on both sides (30 min)
• Step 2 Written case-study - Few questions to check that written communication is clear
• Step 3 Technical case-study - Skills check (take home assignment) on some data problems (no more than 2 hours of involvement)
• Step 3 Visio-call - Debrief from assignment + Experience and background discussion to get to know you and your experience in Data. Interview questions will be sent ahead of time.