DataOps Engineer

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 (e.g., Apache Airflow, Prefect, or Dagster).
• Hands-on experience with cloud platforms (e.g., AWS, GCP, Azure) and cloud-native data tools.
• Familiarity with CI/CD tools (e.g., 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 (e.g., 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 (e.g., via Git).

Nice to have skills

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