Sifflet implements data quality checks ranging from the simple (detecting null values) to the very complex (time series forecasting models to validate that the distribution of a set of columns hasn’t changed in an unexpected way, taking into account seasonality, one-off events…). This foundation is used by many features, such as automatically merging related alerts into incidents.

The monitoring team is responsible for evolving the data quality checks performed by Sifflet, and all related features. As a member of this team, you will:

• design and implement new types of data quality checks

• build features to allow users to efficiently monitor their entire data stack, such as automated monitor suggestions

• design advanced solutions to cut the alerting noise, such as automated incident root cause analysis

• scale our monitoring engine to support more and more customers. Some customers require monitoring massive data sets.

Some projects you could be working on

• add support for automated data profiling (understanding the expected distribution of values in all columns), and build a statistical root cause analysis feature on top of that

• build an API to allow users to submit their own asset quality metrics, and surface unmonitored assets to users

• design and implement automated quality check suggestions

Our stack

• the monitoring engine is built with Python 3 and its large data/ML ecosystem.

• the web API is written in (modern) Java with Spring Boot 3, the web frontend is a VueJS application written in Typescript. You may occasionally need to make minor changes to this code base.

• infrastructure: Kubernetes (AWS EKS clusters), MySQL (on AWS RDS), Temporal for job orchestration.

• and a few supporting services: Gitlab CI, Prometheus/Loki/Grafana, Sentry…

While not directly part of our stack, expect to gain a lot of knowledge on many products in the modern data ecosystem. The subtleties of BigQuery or Snowflake will soon be very familiar to you.

• more than two years of experience in a backend engineer role or equivalent. Data engineers who want to move to a backend engineering position are also welcome.

• general knowledge around some of these topics: data warehouses, data visualisation solutions, ETL pipelines… You don’t have to know everything upfront of course, you’ll pick up what you need on the job.

• willingness to learn Python if you don’t already know this ecosystem.

• you value ownership of your projects from design to production, and aren’t afraid of taking initiatives.

None of the people who joined Sifflet perfectly matched the described requirements for the role. If you’re interested in this position but don’t tick all the boxes above, feel free to apply anyway!

Are we the company you’re looking for?

• We have offices in Paris, but we’re very remote friendly - several team members are fully remote.

• We offer competitive salary and company equity.

• We have experts on many topics, so there’s always someone to help. We also have weekly tech talks where everyone can discuss a cool project or technology.

• We’re constantly exposed to the intricacies of the modern data ecosystem - you’ll become very knowledgeable about data engineering and the modern data stack, and about how data is used in enterprises.

• We’re building a genuinely great product, and we think you’ll love the team!

We believe in a transparent and engaging hiring process to ensure the best fit for both you and our team. Here’s what to expect:

1. Introduction Call – A conversation with a team lead to discuss your background, the role, and what excites you about Sifflet.

2. Technical Interviews – Two in-depth assessments:

   ◦ Coding Interview – Evaluate your problem-solving and coding skills.

   ◦ System Design Interview – Assess your ability to design scalable and efficient systems.

3. Meet the Product team – Gain insights into our vision, challenges, and ambitions.

4. Team Connect – Meet your future colleagues, experience our culture, and see firsthand what makes our team awesome!

5. Reference Call – A final step to gather feedback from previous colleagues or managers.

We aim to make the process insightful and collaborative, giving you a real sense of what it’s like to work at Sifflet