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

DataOps Engineer

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