Role overview

Data Engineer

Requirements and responsibilities

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Your responsibilities:

  • Design, develop, and maintain scalable data pipelines.
  • Build and optimize data infrastructure.
  • Implement data quality monitoring and validation frameworks.
  • Optimize data storage, processing, and query performance for large-scale datasets.
  • Design and implement data models for analytics and reporting use cases.
  • Develop tools and automation to improve data engineering workflows and productivity.
  • Ensure data governance, security, and compliance standards are met.
  • Participate in on-call rotation to support production data systems.

Must-haves:

  • 3+ years of experience in data engineering or related roles.
  • Experience building and maintaining data pipelines using orchestration tools (e.g., Airflow, Prefect, Dagster).
  • Strong proficiency in SQL and solid programming skills in Python.
  • Experience with distributed data processing frameworks (e.g., Apache Spark, or similar).
  • Knowledge of data modeling principles and best practices.
  • Understanding of data architectures and storage systems.

Nice-to-haves:

  • Experience with real-time data streaming platforms.
  • Familiarity with Infrastructure as Code tools (Terraform, etc).
  • Experience with containerization (Docker) and Kubernetes.
  • Knowledge of data governance and privacy frameworks (GDPR, SOC2).
  • Knowledge of data quality and observability tools (Great Expectations, etc.).

Benefits & Perks:

  • Competitive compensation
  • Career growth and learning opportunities
  • Flexibility and ownership
  • Collaborative and innovative culture
  • Opportunity to work on impactful AI projects
  • International environment and talented teams
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Browse stack
FocusData EngineeringRole area
Seniority signalSeniorCandidate level
StackDocker, Kubernetes, PythonPrimary skills
Location42 accepted countriesEligibility

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