Junior Infrastructure Engineer

Posted Yesterday
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Hiring Remotely in France
Remote
Junior
Artificial Intelligence • Big Data • Software • Big Data Analytics
The Role
Join the infrastructure team to maintain and improve cloud infrastructure (primarily AWS, compatible with GCP/Azure), data pipelines, monitoring, developer tooling, and security. Work includes implementing product features requiring infra expertise (agents, Terraform provider), improving performance and scalability, and enabling the engineering/product teams through tools and automation. Junior-level role with wide exposure to software development, data engineering, and cloud operations.
Summary Generated by Built In
About Sifflet

We are building the world’s best data observability platform to help companies excel at data-driven decision making.

Today, half of a data team’s time is spent troubleshooting data quality issues. Sifflet is putting an end to that. Our solution allows data engineers and data consumers to visualize how data flows between their services, define data quality checks, and quickly find the root cause of any data anomaly.

Our product is targeted both at data engineers who want to make sure their pipelines are running smoothly, and at data consumers, who want to be able to trust the data they use to make decisions.

About the job

We’re hiring an engineer to join our infrastructure team. This is a junior-level position (new graduates welcome!) suited for engineers with less than 3 years of experience.

What we call “infrastructure” at Sifflet covers a large area and even some product features. As a result, this team is closer to the product and our customers than comparable teams at other companies. This means you’ll have the opportunity to work on an extremely wide range of topics, including cloud infrastructure, software development, and data engineering.

Specifically, as a member of this team, you will:

  • Maintain the cloud infrastructure of Sifflet. We’re mostly on AWS, but our applications need to be compatible with GCP and Azure.

  • Maintain and improve our data pipeline, including making new sources of data available to our product team for analytics. We of course use Sifflet to monitor Sifflet’s data pipeline.

  • Design and implement monitoring strategies for our applications and systems; improve the performance of our services (we are starting to face scalability challenges).

  • Design and implement product features related to network connectivity with monitored sources (such as a network agent), or where infrastructure expertise helps (such as our Terraform provider).

  • Be responsible for internal developer tooling and platforms, such as on-demand environments to test changes, CI runners, logging pipelines, feature flag services…

  • Ensure the security of our systems, and deploy security good practices.

  • In general, help the whole engineering and product team to be as productive as possible!

Some projects you could be working on
  • Extend the agent that runs in customer networks with support for new sources to be monitored, and contribute to improving the agent management UI.

  • Implement tooling to monitor database performance, and lead an action plan to address the most pressing issues.

  • Ingest infrastructure, product and sales data into a single data warehouse to allow the product team to correlate product usage, revenue and costs for each customer.

  • Reduce our infrastructure costs by migrating our Kubernetes Ingress controller to a more cost-effective architecture.

  • Improve the throughput of our monitoring workers, through a combination of infrastructure changes (improved auto-scaling strategy), architecture changes (less bursty scheduling) and pure code performance optimisations.

Our stack
  • Applications written in modern Java (Spring Boot 3) or Python 3, frontend in Typescript + VueJS, some Go (Terraform provider).

  • Infrastructure: Kubernetes (AWS EKS clusters), MySQL (on AWS RDS), self-hosted Temporal clusters for job orchestration.

  • Data stack: streaming data pipeline using change data capture from the production MySQL databases to a Snowflake account; dbt, Dagster Cloud; Omni for visualization.

  • Supporting services include Gitlab CI, self-hosted Victoria Metrics + Grafana Cloud, Sentry…

While not directly part of our stack, our product integrates with many different services in the modern data stack ecosystem and you’ll pick up some knowledge on many of these services.


Preferred qualifications
  • Software engineering degree or equivalent relevant experience. This position is open to new graduates.

  • Some general knowledge around these topics: web architecture, data engineering, cloud infrastructure… Of course, you don’t have to know everything upfront, you’ll pick up what you need on the job.

  • We’re looking for engineers that are willing to learn many different areas quickly and don’t consider anything as “out of my scope”. This position requires working on Python, Java and Go codebases, and includes a significant share of software development and data engineering on top of the usual infrastructure work.

  • You take ownership of your projects from design to production, and aren’t afraid of taking initiatives. We value autonomy (a lot!), but we have a strong team that’s always available to help.

This is an on-site position in our Paris office (rue de Châteaudun) with flexible remote work allowed a few days per week.

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 a multi-cultural team with nationalities from multiple continents; expect office banter in either French, English, or Spanish.

  • We offer a competitive salary and company equity.

  • We have experts on many topics, so there’s always someone to help. We also have 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.

  • Our culture emphasises teamwork to efficiently deliver projects to production.

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

Interview process
  • A first 30 minutes call with Benoît (Head of Engineering) to discuss the position and ensure it matches what you’re looking for.

  • One coding interview (1h30) where we design and implement together a solution for a project specific to Sifflet. We ask you to have your favorite development environment for the language of your choice ready. Based on our experience, we recommend you don’t use AI coding tools in this exercice.

  • One system design interview (1h30) where we discuss how to solve a case study inspired by Sifflet’s domain.

The interviews are held remotely to speed up the process.

We‘re happy to organise any session that would help you make a decision once you get an offer: lunch with the team, 1-1 discussions with an engineer…

Skills Required

  • Less than 3 years of professional experience / new graduate welcome
  • Willingness to work on and contribute to Python, Java and Go codebases
  • Maintain cloud infrastructure primarily on AWS, with compatibility for GCP and Azure
  • Familiarity with Kubernetes (EKS) and container orchestration
  • Experience or familiarity with Terraform and infrastructure-as-code
  • Experience with data pipelines, MySQL and change data capture workflows
  • Familiarity with monitoring and observability tooling (Victoria Metrics, Grafana, Sentry)
  • Software engineering degree or equivalent relevant experience
  • General knowledge of web architecture, data engineering, and cloud infrastructure
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The Company
42 Employees

What We Do

Sifflet is a cloud-native data observability platform that gives data teams end-to-end oversight of their data stack. It detects anomalies, diagnoses root causes, and ties technical issues to business impact so teams can trust data used for dashboards, models, and decisions. Sifflet’s tooling aims to reduce data breaks, improve alignment, and make data reliable for AI and business use.

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