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IMC

Site Reliability Engineer - Data Platform

IMC is hiring a Site Reliability Engineer - Data Platform in Amsterdam, Netherlands. Level rates it ; you can apply on IMC.

Level's read on this job

  • Level rates this role Little AI ●○○○: aI is not part of the work.
  • The posting mentions Kafka, Hadoop and Spark among its tools and skills.
  • Level classes it as a senior role.
  • IMC has 155 other open roles on Level.

AI in this role

Manage and scale distributed data platforms on Kubernetes and bare metal while improving automation and observability.

KafkaHadoopSparkDremioKubernetesAnsiblePythonSQLAirflow

IMC operates on the cutting-edge use of technology to create a competitive edge over the competition. We also grow quick and have plenty of complex technical challenges. We're looking for an experienced SRE with strong background in managing distributed data systems on both bare metal Linux and Kubernetes. We want someone who can help us standardize deployments, elevate observability, and improve automation as we scale our data platform and other critical data services.

You will join our Data Platform team, part of our local data team that builds and runs the systems that are used by traders, quant researchers and engineering teams, for all their data needs. The Data Platform team is responsible for the foundational platform that our data frameworks and tooling is built on top of. This includes observability, scalability and supporting standardised deployments.

Your Core Responsibilities:

As an SRE within IMC you will join a sub-team that takes a central role in all the data needs and you’ll be working to:

  • Design, implement and operate our data platforms.
  • Improve observability so we catch issues before our users do.
  • Build automation to reduce toil and allow our systems to scale
  • Support and own reliability of critical services (e.g. HDFS, Kafka and Dremio)
  • Drive long-term architectural improvements, not just fixing issues, but preventing them.

Your Skills and Experience:

  • Strong experience managing distributed data platforms (e.g. Kafka, Hadoop, Spark, Dremio); including full installation, debugging and performance tuning
  • Hands on experience deploying, configuring and orchestrating software on Linux and Kubernetes, with proven ability to troubleshoot issues in both environments
  • Strong experience with infrastructure as code (Ansible preferred) and best practices
  • Proficient programming experience in Python
  • Ability to read, write and tune SQL queries
  • Comfortable reading Java source code, tuning and debugging running JVMs.
  • Familarity with data lakehouse technologies (e.g. Iceberg or Delta Lake) as well as query engine technologies (e.g. Dremio, Presto or Trino)
  • Exposure to workflow orchestration tools like Airflow or Dagster
  • A proactive mindset: you're not just fixing issues but preventing them.
  • Comfortable working across teams, with minimal oversight.

Our Tech Stack:

  • Data Tools: Hadoop (HDFS), Kafka, Dremio, Iceberg, Clickhouse, Spark, Airflow, Flink
  • Infrastructure Automation: Ansible, Puppet, Kubernetes (ArgoCD, Helm, Kustomize)
  • Observability: Prometheus, Grafana, AlertManager
  • Scripting: Python, Bash, SQL
  • Others: PCAP infrastructure

About Us

IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.

How we rate this

Site Reliability Engineer - Data Platform at IMC rates 0 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

KafkaHadoopSparkDremioKubernetesAnsiblePythonSQL

Questions you could be asked

  1. What's a project where you used Kafka hands-on?
  2. Walk me through how you've used Hadoop in your day-to-day work.
  3. What are the limits of Spark that you've run into, and how did you work around them?
  4. What's a project where you used Dremio hands-on?
  5. Walk me through how you've used Kubernetes in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Kafka, Hadoop, Spark, Dremio, and Kubernetes. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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