Data Engineer | Talent Program

at  Mploy Associates

LET’S TALK TALENT

You have talent. Ready to make impact. We know. We also know that making impact starts with that first contact between likeminded people who have the same drive to shape their future. We see you, with your skills, personality and dreams. Now let’s take it to even greater heights by means of one of our talent programs for master’s graduates.
We are Mploy Associates, a talent focused consultancy firm ready to make not only our clients’ teams successful but also you. Your talent, our focus.

WHAT ARE WE LOOKING FOR?

We are looking for graduates with different data and IT-related backgrounds, experiences, and passions. It speaks for itself that you are ambitious, self-reflective and dare to be confident in an authentic way.

Furthermore, you are energized by stakeholder management and are well adept at gathering reliable information. You use this in combination with a consultive mindset to make our clients more successful. Last but not least, you are eager to develop yourself on personal, professional and technical level with our personalized in-house Talent Programs. To make it more specific:

• You have 0-3 years of work experience and want to learn everything about data engineering;
• You want to put the skills into practice that you have acquired during your master’s in Computer Science, Data Science or another related study;
• You are familiar with one or more operating systems (e.g. Linux, Unix, Windows), cloud platforms (e.g., Azure, AWS, Google Cloud) and common programming languages (e.g., Java, SQL, Python, C#);
• You do not hesitate to use your analytical skills to solve complex problems creatively and logically.

• Supervising the technical implementation of data elements, from raw to cleansed data;
• Making an inventory of the relevant databases within the organisation and gaining access to them;
• Developing and maintaining scripts, tools and applications based on different languages and structures (e.g., Python, PySpark, Java);
• Migrating projects between different environments (e.g. from Hadoop to Azure);
• Documenting and presenting the implemented dataflows to relevant stakeholders