Data Platform Engineer

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

📋 Description

• Create and implement cloud-based data platform infrastructure utilizing Infrastructure as Code (Terraform).

• Develop and sustain CI/CD pipelines that automate workflows in data engineering, deployment of data pipelines, and provisioning of infrastructure.

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

• Work collaboratively with data engineers and cross-functional teams to design and execute data pipelines, data models, and platform features that satisfy performance and business requirements.

• Employ best practices for ensuring high availability, disaster recovery, security, and cost efficiency, while documenting infrastructure patterns, data architecture choices, and operational procedures.

⛳️ Requirements

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

• Demonstrated success in designing and implementing reliable and scalable data platforms and data infrastructure.

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

• Proficient in Infrastructure as Code (Terraform) and cloud architecture models on AWS or GCP.

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

• Hands-on experience with Kubernetes and containerized workloads for managing data platform services.

• Familiarity with implementing observability stacks for monitoring, logging, metrics, and alerting in data platforms.

• Strong programming abilities in Python, SQL, and Bash for building data pipelines, automating workflows, and executing data processing tasks.

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

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

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

🏝️ Benefits

• Health insurance

• Flexible working hours

• Professional development opportunities