Data / Back-end Engineer (Python, Spark, Kafka, ...)
- Début :
- Télétravail partiel possible
- > 3 ans
- Artificial Intelligence / Machine Learning, Big Data, Commercial Real Estate
- De 15 à 50 salariés
Data / Back-end Engineer (Python, Spark, Kafka, ...)
Square Sense is a fast-growing platform that provides advanced data solutions to global real estate asset managers and investors. We build AI-powered “building brains” that support the digital transformation of investment and asset management and improve the operational and financial performance of real estate assets.
Square Sense was founded in 2017 in Paris by a multi-cultural team of talented engineers and data scientists.
Software Engineering at Square Sense
In Square Sense’s Software Engineering Team 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 to access it (analytics platform), or use third-party APIs to manipulate the physical world (automated decision making solution).
Our main programming languages are Python & Scala. Our solution is built with modern technologies such as (list is not exhaustive): Docker and Kubernetes, Kafka stack (Kafka, Kafka Connect, KSQL), Spark, Airflow. 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, and 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 / Back-end Engineer 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 / Back-end Engineer are:
- In collaboration with fellow team members, design the data pipelines for collection, storage, processing and BI of data generated by IoT devices and third-party services. Propose relevant technologies and solutions.
- 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 Data Engieenrs and Back-end Engineers in architecture design and implementation, with Data Scientists to support the research activities, and with DevOps Engineers to deliver to production all software you develop.
We are looking for a software engineer with 3+ years of professional/industry experience. Candidates for this position are expected to have:
- Strongly engineering-oriented profile.
- At least 3 years full-time job experience is mandatory.
- Willingness to work in a rich technical environment where Data Engineering joins full stack software development and DevOps.
- Industry experience and strong programming skills in Python. Additional experience in Scala is a big plus, but not mandatory.
- Experience with Apache Spark. Additional experience with other data processing frameworks is a big plus.
- Experience in data modelling: design of robust data models, data lake, and database schemas.
- A taste for high quality software (clean code, high test coverage, willingness to do thorough PR reviews).
- Industry experience with multiple (more than one) products from a business standpoint.
Knowledge in all of the following areas is a plus:
- Docker, Kubernetes
- Kafka stack (Kafka, Kafka Connect, KSQL, Kafka Streams)
- SQL and NoSQL databases, graph databases
- 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
- A team leader 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)
- 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.
Meet the Square Sense team
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