Position: Data Engineer with Azure
Company: Intellias
Category: Data Engineer
Experience required: 1y
English level: upper

Our client is a leading private equity firm specializing in investments in software, e-commerce, and technology-enabled businesses. With a rich history dating back to 2003, the company has established itself as a prominent player in the industry.

At the company, we believe in the power of innovation and the transformative impact of technology. One of our core initiatives involves collecting market research, conducting interviews, and aggregating data from multiple sources to understand and oversee global economy and market trends. This project plays a crucial role in informing our investment decisions and driving strategic initiatives.

As a data engineer at the company, you will play a vital role in supporting this project. You will be responsible for designing, building, and maintaining the data infrastructure and pipelines that enable the collection, processing, and analysis of diverse data sets. By ensuring the availability, reliability, and security of our data assets, you will empower our team to derive meaningful insights and make data-driven decisions.

Expectations:
One year or more of experience in the field.
Most of the work will be in SQL, so being skilled in SQL is a requirement
Experience in Azure data services (preferably Synapse, Databricks, ADF, Azure Storage, and Purview) and a proven track record of delivering high-quality data solutions in a fast-paced environment
Experience in Python to write custom pipelines if necessary
Good understanding of data modeling, normalization, fact vs dimension tables, and so on
Works well in a setting where he or she needs to make sure the principles and requirements are met, but where speed is valued over extreme scalability
Actively use AI pair programmer, such as Github Copilot

Wishes:
Familiar with data/dev ops principles (versioning, ci/cd, automated tests, etc)
Familiar with the Microsoft data stack (know about the possibilities in data factory, purview, anomaly detection, key vault, etc)
Advantage if they have experience with dbt (https://www.getdbt.com/), but it is mostly just SQL so can easily be learned if they know SQL and data modeling
We might want to do some work in Spark, so knowing that is an advantage, but not a requirement
Be a driving force for good data governance

Degree: Specialist / Professional Certified