Square Sense

Square Sense

Internship: Data Engineer / ML Engineer (Python, Spark, Kafka, ...)

  • Plný úvazek 
  • Počáteční datum:  
  • Paris
  • Možnost pracovat částečně z domova
  • < 6 měsíců


Square Sense

Square Sense

  • Artificial Intelligence / Machine Learning, Big Data, Commercial Real Estate


Internship: Data Engineer / ML Engineer (Python, Spark, Kafka, ...)

  • Plný úvazek 
  • Počáteční datum:  
  • Paris
  • Možnost pracovat částečně z domova
  • < 6 měsíců


Square Sense was founded in 2017 to lead the digital transformation of real estate asset management.
We combine skills in data science, software development, and asset management, delivering cutting-edge applications to transform real estate into a data-driven industry.

Job description

Software Engineering at Square Sense

Our Software Engineering team has a combined skillset that covers data engineering, full-stack web development, site reliability engineering, and quality assurance. We are responsible for implementation, quality control, delivery and maintenance of the Square Sense software solution and data lakehouse, as well as providing ongoing support of data-related activities.

We are building a multitude of products in the domains of data collection, analysis, visualization and IoT manipulation. Our systems collect data from IoT devices and third-party data sources, process ingested data in streaming and batch modes, organize processed data, provide the APIs and UI to access it (analytics platform), or use third-party APIs to manipulate the physical world (automated decision making solution).

Our main programming language for data products is Python. Our data processing back-end is built on Spark, Airflow, PostgreSQL, Docker, Kubernetes, with bits of Hadoop and Kafka, and includes a multitude of data processing applications. Our production platforms run in the public clouds (Azure, GCP, AWS) and employ related services such as GKE, Dataproc (GCP) and AKS, HDInsight (Azure) to name a few. We deploy the software in a Continuous Delivery process. We focus on a high quality of our software and all team members take seriously such practices as automated testing and PR reviews.

All team members participate in the design and architecture, development, quality, production delivery, and monitoring.


As a Data / ML Engineering intern you will be a member of the Software Engineering Team. This position implies close collaboration with all members of the Software Engineering Team, as well as members of our Data Science Team, who design and implement various data processing algorithms.

Primary objectives of a Data and ML Engineer are:

  • Design and develop multiple software components for data collection (connectors for various IoT devices and third-party services, web hooks) and ingestion of collected data (using Kafka, for example).
  • Design and develop multiple software components for data processing (for example, streaming and batch data pipelines with Apache Spark or Apache Kafka Streams), as well as other internal software, tools and APIs to support the data processing.
  • Automate data processing tasks and their monitoring in production (for example, orchestration of batch processing jobs using Airflow).
  • Design efficient data models using various storage technologies (cloud file storages, HDFS, relational DBs and non-relational DBs).
  • Collaborate with DevOps Engineers for production delivery and related objectives.

Preferred experience


We are looking for a student interested in data engineering that is studying for a postgraduate degree in engineering, a master (M2), or an equivalent university course and is looking for a final 6-month internship.
Candidates for this position are expected to have:

  • Strongly engineering-oriented profile. (Please, note that this position is not suitable for the typical requirements of research internships, and is oriented towards software engineering).
  • Willingness to work in a rich technical environment where Data Engineering joins full stack software development and DevOps.
  • Strong programming skills in Python. Experience with other languages is a plus.
  • Some epxerience and understanding of Apache Spark. Experience with other data processing frameworks is a big plus.
  • Experience with SQL.
  • A good taste for high quality software. Rigor.

Knowledge in all of the following areas is a plus:

  • Scala
  • Docker, Kubernetes
  • Kafka stack (Kafka, Kafka Connect, KSQL, Kafka Streams)
  • Cloud Platforms (AWS / GCP / Azure)
  • Agile (Scrum) or Lean (Kanban)

Being passionate about IT ourselves, we are looking for a likewise passionate person with a good team spirit.

What we offer

  • An experienced engineering team with a very strong high-quality development mentality yet focused on fast and agile execution to achieve business impact
  • A data-centric product, where engineers make an important contribution to making it all happen
  • Team leaders with more than 10 years of professional experience in software engineering
  • A competitive salary and eligibility for participation in the stock option plan.
  • Performance-based bonuses
  • Fast-growing early-stage startup
  • A multi-cultural team that is passionate about technology, regular team outings
  • Open communication, flat hierarchy, and fast execution
  • A budget for personal education, participation to conferences, and training
  • Flexible working hours
  • Remote work possible: we are currently fully remote during the COVID-19 pandemic; in the long-term we plan to work remotely up to 3 days out of 5
  • A comfortable office in the center of Paris (Strasbourg – Saint-Denis metro station)

Recruitment process

  1. Phone call, about 30 minutes. The objective of the phone call is to confirm the intent to continue the process.
  2. Technical exercise. The exercice is fully asynchronous and remote, with no deadline. It usually takes about 4 hours end to end.
  3. Technical and general interview. It includes lots of pair programming, coding and design, some theory, some general questions, no whiteboard programming or trick questions. Remote or in the office. Plan 2 hours at least.
  4. Meeting with the Team: meet co-founders and more team members.

Depending on how tight we scheduled these steps, the whole process may take from 1 to 3 weeks.

Meet the team

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