Data Engineer

• Do you love to work on various projects and implement end-to-end data solutions?
• Are you ready to expand your skillset in different tools, methodologies, and across various industries?
• Do you have an innate passion for all the technical aspects of a data project while having an entrepreneurial sense in building a new practice within a consultancy company?

As a Data Engineer, you will play a key role in tackling complex technological projects for our most challenging assignments. You will play a key role in preparing the (big) data infrastructure used by our Data Scientists in the delivery of our projects.

What will you do day-to-day?

• Conceive and build maintainable (cloud) data architectures (infrastructure, ETL, infra-as-code…)
• Integrate data sources by developing data pipelines
• Create large data warehouses and datamarts fit for further reporting or advanced analytics
• Monitor the quality and stability of data solutions
• Optimize data ecosystems' performance & costs
• Support Agilytic Data Scientists & Data Analysts in deploying data solutions for the clients
• Stay up to date with the latest developments in data technology
• Coach and actively share your knowledge with your colleagues

Requirements

We are looking for strong candidates with the following academic and professional experiences. Don’t worry if you don’t thick all the boxes, and let’s talk if your motivation is there.

Your background

• A Master in Computer Science, Engineering, Mathematics, Statistics or another quantitative discipline
• Ideally 2+ year demonstrated experience with big data platforms (Hadoop, Cloudera, EMR, Databricks...), cloud environments (Azure, AWS, or GCP) or end-to-end BI projects.
• But being eager to learn new topics in the Data Engineering field is what matters most !

Your skills

• Technical knowledge in one or more of the following competencies
• Data pipeline management/ETL processing
• Database management (SQL and noSQL databases)
• Data modeling basics (3NF, Star Schema…)
• Large file storage (HDFS, Data Lake, S3, Blob storage…)
• Cloud platforms management like AWS, Google Cloud or Azure, in a data context
• Docker
• DevOps best practices integration (CI/CD, Infra-as-Code, unit testing…) is a plus
• Workflow management such as Airflow or Oozie is a plus
• Stream processing such as Kafka, Kinesis, Elasticsearch is a plus
• Programming languages requirements
• Working experience with Python, SQL, and/or R (Java, Scala are also considered)
• Knowledge of Spark with Scala or Pyspark is a plus
• Other requirements
• Fluency in English
• Fluency in either in French OR Dutch
• Eligibility to work in Belgium and the European Union (please be aware that we cannot provide relocation support)

Your Growth Path

• As a consultancy company, people are at the core of what we do. We will therefore guide you and give you the support you need to develop and grow. However, we equally believe that it is you who takes ownership of your growth. That is why you will be the main actor of your Individual Growth Plan.
• As an agile and problem-solving minded company, you’ll be facing many opportunities to deepen your technical expertise in one domain or broaden your perspective in the data world.

What we expect from you

• Problem-solving mindset and pragmatic approach
• Innate care about work quality
• Curiosity about new techniques and tools, eagerness to always keep learning
• Desire to be among the first employees of a growing Data Engineering structure, to help us shape our organization in the future

Some signs this may not be the right fit

• If you don't like to interact with customers or do presentations from time to time: all our data engineers are client-facing
• If you’re not comfortable working on premise (on average 2-3 days a week), being at the client premises or from our offices in Brussels.
• If you aren’t ready to go the extra mile to deliver quality work and help us build a great team together

Benefits

Working at Agilytic

We aim at creating a work environment that allows you to do great work, grow your skillset and, most importantly, be happy while doing it.

We believe that data is a means to an end and not an end. We don’t use cutting-edge techniques when not suited to the problem we need to solve. We adapt to what the client truly needs, even if it might look less appealing from a technical perspective. <