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Internship: Data Engineer / ML Engineer (Python, Spark, Kafka, ...) Square Sense
Permanent
Paris
A few days home
Salary: Not specified
< 6 months
You'll be part of
33 employees
Artificial Intelligence / Machine Learning
Big Data
Commercial Real Estate
Average age: 32
Founded in 2018
60%
40%
Employee turnover: 1
Square Sense développe des solutions destinées aux grands investisseurs immobiliers (foncières, institutionnels, fonds d’investissement) pour les aider à faire face aux nombreux enjeux auxquels ils sont confrontés et leur permettre d’adapter leurs stratégies de gestion d’actifs plus rapidement et plus efficacement.
Pour ce faire, ces solutions interprètent des données collectées dans les immeubles à partir de plusieurs sources : gestion financière, énergie, IoT, services aux usagers, community management, etc. Elles permettent de comprendre les attentes des locataires et usagers, mesurer leur satisfaction et anticiper les situations à risque, et ainsi permettre aux gestionnaires d’actifs de prendre les bonnes décisions au bon moment. Ces solutions ont pour finalité d’améliorer la performance financière des actifs et leur impact sociétal et environnemental.
La plateforme développée par Square Sense met en oeuvre les technologies incontournables en matière de traitement de données massives. Son équipe de data scientists utilise les techniques de pointe en apprentissage automatique pour développer ses applications data-driven.
Square Sense a été fondé en 2018 à Paris par une équipe multiculturelle et talentueuse d’ingénieurs et de scientifiques.
You'll be working on
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.
Objectives
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.
We're looking for
Profile
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: every team member has a choice of working remotely, in the office, or mix the two; today, most of us work four days a week remotely, and one day a week in the office
- A comfortable office on boulevard du Montparnasse with a nice view over Paris
How we hire
- Phone call, about 30 minutes. The objective of the phone call is to confirm the intent to continue the process.
- Technical exercise. The exercice is fully asynchronous and remote, with no deadline. It usually takes about 4 hours end to end.
- 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.
- 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.
Key figures
In short
Founding year
2018
Employees
33
Average age
32
Turnover rate
1
Gender
40%
60%
