Data Engineer
Core
Design, deploy, and evolve robust data platforms to handle large volumes of data and operationalize advanced AI and machine learning use cases.
Role type
Data Engineer
Builds
Data platforms, ingestion/transformation pipelines, and ML-integrated solutions for clients and internal products.
Domain
Artificial Intelligence, Data Engineering, Software Engineering
Deliverable
production ML models | product features | infrastructure
Required skills
Python, Java, Scala, or Kotlin; SQL; batch and streaming data processing; relational and NoSQL databases; Git and CI/CD pipelines; Docker containerization
Preferred skills
AWS, GCP, Azure, Databricks, or Snowflake; MLOps/ML Engineering tools; Kubernetes, Terraform, or Ansible; unit and integration testing; back-end development; machine learning or data science basics; Unix/Linux environments
Technologies
Python, Java, Scala, Kotlin, SQL, Git, Docker, AWS, GCP, Azure, Databricks, Snowflake, Kubernetes, Terraform, Ansible
Responsibilities
Design and implement large-scale data ingestion, transformation, and exposure pipelines; Define and implement performant data architectures (data lake, warehouse, lakehouse); Industrialize solutions integrating machine learning or AI models; Participate in technology choices and data ecosystem evolution; Mentor other data engineers; Interact with product teams, business units, and clients; Contribute to cross-functional initiatives like R&D and automation
Seniority
Mid-level, hands-on IC with mentorship responsibilities
