Data Platform Engineer

This is a fully remote position, open to applicants in Serbia.

📋 Description

• Design and establish cloud-based data platform infrastructure utilizing Infrastructure as Code (Terraform), with a strong emphasis on scalability, security, reliability, and cost-effectiveness.

• Develop and sustain CI/CD pipelines that automate data engineering workflows, data pipeline deployments, and infrastructure provisioning to ensure quicker deployment cycles and reduce errors.

• Implement and manage observability solutions by integrating monitoring, logging, and metrics to guarantee platform reliability, performance visibility, and prompt incident response.

• Work collaboratively with data engineers and cross-functional teams to design and execute data pipelines, data models, and platform capabilities that align with performance and business needs.

• Apply best practices for high availability, disaster recovery, security, and cost optimization, while documenting infrastructure patterns, data architecture decisions, and operational processes.

⛳️ Requirements

• 3-5 years of practical experience in Data Engineering, Platform Engineering, or DataOps positions.

• Demonstrated success in designing and implementing dependable, scalable data platforms and data infrastructure — taking ownership of end-to-end delivery.

• Proficient experience with contemporary data engineering tools such as dbt, Apache Airflow, or Apache Kafka is essential.

• Hands-on expertise with Infrastructure as Code (Terraform) and cloud architecture patterns on AWS or GCP.

• Extensive experience with AWS or GCP, including data storage and processing services (e.g., BigQuery, Snowflake, S3, Redshift).

• Practical knowledge of Kubernetes and containerized workloads for orchestrating data platform services.

• Experience in implementing observability stacks for monitoring, logging, metrics, and alerting within data platforms.

• Strong programming capabilities in Python, SQL, and Bash for building data pipelines, automating workflows, and conducting data processing.

• Exceptional problem-solving abilities and the capacity to work effectively in a collaborative, fully remote setting.

• A strong desire to enhance expertise in data architecture, data modeling, and MLOps capabilities.

• Familiarity with real-time data processing (e.g., Kafka, Spark Streaming) and both SQL and NoSQL data storage solutions is a plus.

🏝️ Benefits

• Health insurance

• 401(k) matching

• Flexible work hours

• Paid time off

• Remote work options