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MLOps | Data Engineer
Remote | Full-time
Role Responsibilities:
- Design, develop, deploy, and manage AWS infrastructure for the Data Science / Machine Learning team
- Build and maintain data acquisition pipelines (API, web scraping, databases)
- Develop, deploy, and manage BI tools (Power BI, Looker, Metabase, Grafana)
- Ensure data security across all systems
- Manage OLAP systems for analytical processing
Required Skills & Experience:
- 5+ years in IT operations and cloud infrastructure management (AWS)
- Solid knowledge of ML services (Amazon SageMaker, Amazon Bedrock, and others)
- Experience with IaaC development (Terraform) and infrastructure automation (Docker, Kubernetes)
- Hands-on experience with repository management, branching strategies, and CI/CD (Bitbucket)
- Experience with data lakes (AWS S3) and databases (PostgreSQL, ClickHouse), proficient in SQL, understanding of OLAP
- Hands-on experience with data pipeline management and ETL processes
- Strong experience with BI tools (Power BI, Looker, Metabase, Grafana)
- Proficient in Python for automation of data pipelines
- Upper-Intermediate (B2+) or higher level of English
Would be a Plus:
- AWS certifications (e.g., AWS Certified DevOps Engineer)
- Experience with Azure and/or GCP
What We Offer:
- Career growth within an international team working on an interesting product with a proven track record
- Competitive salary and financial stability
- Flexible working hours (Mon–Fri, 8 hours/day)
- Free English courses and an education budget for professional development
Key Skills
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