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Senior Data Engineer – Cloud Infrastructure & Platform Engineering

Pauwels Consulting

Paris · Hybrid Full-time Senior 1mo ago

About the role

About

Our client is looking for an autonomous professional to strengthen their data platform capabilities. The project involves maintaining a modern infrastructure, managing cloud environments, and optimizing high-velocity data ingestion pipelines within a distributed architecture.

Responsibilities

  • Manage a complex Airflow architecture deployed via Helm on EKS to ensure robust orchestration.
  • Refactor custom batch DAGs toward event-driven ingestion using Snowpipe to improve cost-efficiency.
  • Support the migration of specific workflows to AWS Managed Airflow while navigating technical integration hurdles.
  • Optimize CI/CD pipelines and infrastructure using Terraform, Vault, and GitHub Actions.
  • Resolve deployment bottlenecks and schema locking issues within automated Flyway workflows.
  • Contribute to the foundational MLOps infrastructure by containerizing data science logic.

Requirements

  • You bring 8+ years of experience in data engineering with a focus on platform stability and scalability.
  • You possess expert knowledge of Python and SQL for complex data processing.
  • You have 8+ years of experience with Snowflake, including advanced data loading and performance optimization.
  • You bring deep expertise in AWS, specifically managing EKS troubleshooting, diagnostics, and S3 storage.
  • You possess extensive experience with Apache Airflow orchestration and distributed streaming via Kafka or Confluent.
  • You have hands-on experience with Terraform, GitHub Actions, and Flyway for infrastructure as code and deployment automation.
  • You're familiar with dbt for data transformation and Datadog for platform observability.
  • You bring the ability to operate autonomously and resolve complex technical bottlenecks in an interim capacity.
  • You're a proactive communicator capable of partnering cross-functionally with analytics and data science teams.
  • You are fluent in English.

Nice to Haves

  • Experience with MLOps and containerizing machine learning lifecycles.
  • Knowledge of Helm for Kubernetes deployments.
  • Familiarity with Jenkins and Vault integrations.

Offer

  • Start date: ASAP
  • Duration: 6 months
  • Work regime: Full-time
  • Location: Paris or Berlin
  • Working model: Hybrid (3 days onsite)
  • Contract: open to both permanent employees and freelancers

Skills

AWSAWS EKSApache AirflowConfluentDatadogDockerFlywayGitHub ActionsHelmKafkaMLOpsPythonSQLSnowflakeTerraform

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