Senior Data Engineer at HyperGuest

Reims, Grand Est, France -

Full Time

Start Date

Immediate

Expiry Date

22 Aug, 26

Salary

0.0

Posted On

24 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

ClickHouse, Kafka, Kinesis, Spark, TypeScript, AWS, SQL, Distributed Systems, Data Pipelines, SQS, RabbitMQ, MySQL, CI/CD, Data Modeling, Real-time Stream Processing, Cloud Infrastructure

Industry

Hospitality

Description

We are looking for a Senior Data Engineer with expertise in scalable data platforms and distributed systems to join our dynamic team. You will play a key role in building HyperGuest’s data platform from the ground up, creating the infrastructure, pipelines, and real-time processing systems that will power our products and business insights. This is a unique opportunity to shape both the company’s data architecture and its data-driven culture. Responsibilities Design, build, and maintain scalable data pipelines and cloud-based data infrastructure in AWS. Build systems capable of processing and analyzing petabytes of data in distributed production environments. Own and evolve the analytical data warehouse on ClickHouse — schema design, ingestion pipelines from Kafka/Kinesis/S3, materialized views, query performance, and cost control at large scale. Develop real-time stream processing solutions using Kafka, Kinesis, and Spark. Design and manage distributed messaging and queue-based systems (SQS, RabbitMQ, etc.). Collaborate with engineering, product, and business teams to deliver impactful data solutions and actionable insights. Drive a data-first culture by promoting best practices and enabling smarter, data-driven decision-making across the company. Develop backend services and integrations using TypeScript and modern cloud-native technologies. Improve data reliability, observability, scalability, and operational efficiency. Participate in architecture and strategic technology discussions that shape the future of HyperGuest’s platform. Requirements 4+ years of experience in Data Engineering, preferably in start-up companies. Hands-on experience with ClickHouse (or comparable columnar OLAP engine) Hands-on experience with stream processing technologies (Kafka, Kinesis, Spark). Hands-on experience with queues and messaging systems (SQS, RabbitMQ, etc.). Strong SQL knowledge and experience designing and optimizing complex queries and data models – mandatory. Strong hands-on experience with TypeScript. Experience building and maintaining large-scale distributed systems and data pipelines. Experience with AWS cloud infrastructure and modern CI/CD workflows. Familiarity with relational databases such as MySQL. Strong problem-solving skills, ownership mindset, and a “can do” attitude. Detail-oriented with a strong commitment to quality.

Responsibilities

Design and build scalable data pipelines and cloud-based infrastructure on AWS to power business insights. Own the analytical data warehouse on ClickHouse and develop real-time stream processing solutions.