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DataOps Engineer

DataOps Engineer

IntellectsoftPoland
2 dni temu
Opis pracy

Join our team in building a modern, high-impact Analytical Platform for one of the largest integrated resort and entertainment companies in Southeast Asia. This platform will serve as a unified environment for data collection, transformation, analytics, and AI-driven insights—powering decisions across marketing, operations, gaming, and more.

You’ll work closely with Data Architects, Data Engineers, Business Analyst and DevOps Engineers to design and implement scalable data solutions.

Requirements

  • Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
  • 3+ years of experience in DataOps, DevOps, or Data Engineering roles.
  • Proficiency in scripting languages (Python, Bash, etc.).
  • Strong experience with orchestration tools (, Apache Airflow, Prefect, or Dagster).
  • Hands-on experience with cloud platforms (, AWS, GCP, Azure) and cloud-native data tools.
  • Familiarity with CI / CD tools (, GitLab CI, Jenkins, CircleCI).
  • Knowledge of containerization and orchestration technologies (Docker, Kubernetes).
  • Experience with infrastructure-as-code tools (Terraform, CloudFormation).
  • Strong understanding of data privacy, security, and compliance practices
  • Experience with modern data warehouses (, Snowflake, Redshift, Yellowbrick) and ETL / ELT tools.
  • Understanding of data governance, metadata management, and data cataloging tools.
  • Experience collaborating in Agile / Scrum teams and working with version-controlled data models (, via Git).

Nice to have skills

  • Experience with real-time data processing (, Kafka, Spark Streaming).
  • Familiarity with data observability platforms (, Monte Carlo, Datadog, Great Expectations).
  • Experience working in regulated industries (, gaming, finance, hospitality).

    • Responsibilities :

  • Design, build, and manage CI / CD pipelines for data applications, models, and pipelines.
  • Develop and maintain infrastructure-as-code (IaC) for data platform components.
  • Automate data quality checks, validation, and monitoring processes.
  • Collaborate with data engineers and analysts to optimize data ingestion and transformation pipelines.
  • Implement robust logging, alerting, and observability tools for data pipelines.
  • Manage orchestration frameworks (, Airflow) and ensure timely execution of workflows.
  • Maintain compliance with data governance, privacy, and security policies.
  • Support and troubleshoot production data issues and infrastructure outages.

    • Benefits

  • 35 absence days per year for work-life balance
  • Udemy courses of your choice
  • English courses with native-speaker
  • Regular soft-skills trainings
  • Excellence Сenters meetups
  • Online / offline team-buildings
  • Business trips
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    Engineer • Poland