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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** NAUT SOFTWARE FOUNDATION INC. - **Location:** Belgrade, MT, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Microsoft Azure, BigQuery, Cloud Computing, Cloudera Impala, Computer Engineering, Continuous Integration, Data Infrastructure, Extract Transform Load (ETL), Data Warehousing, Relational Databases, Apache Hive, Python (Programming Language), Machine Learning, RabbitMQ, SQL Databases, Teradata SQL, Data Storage Management, Google Cloud, Azure Data Factory, Snowflake, Data Lakes, Information Technology, Google Bigquery, Integration Frameworks, Apache Kafka, Machine Learning Operations, Presto, Stream Processing, Data Pipelines, Sql Tuning, Amazon Redshift, Databricks, Programming Languages - **Published:** September 18, 2026 - **Apply:** https://nordeus.com/open-positions/engineering_&_science/8213128 ## About the Role * Have a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience * Have minimum 6 years of experience with: + Python or other modern programming languages + SQL and relational databases experience + Custom ETL design, implementation and maintenance * Have minimum 4 years of experience with: + Workflow orchestrators such as Airflow, Prefect, Dagster, Astronomer, AWS Step Functions, Azure Data Factory, or similar + Data Warehouse Modeling * Have experience working with a cloud or on-premises Big Data platform such as Google BigQuery, AWS Redshift, Azure Data Warehouse, SnowFlake, Databricks, Teradata, Hive, Presto or similar * Have experience working with stream processing platforms such as Kafka, Google Pub/Sub, Amazon Kinesis, Azure Events Hub, RabbitMQ and similar BONUS POINTS: * Experience with public cloud providers GCP/ AWS/ Azure * Experience querying petabyte-sized datasets using BigQuery, Trino, Hive, Impala, etc. * Experience designing and implementing real-time pipelines * Experience with data quality and validations * Experience with SQL performance tuning * Experience with anomaly/outlier detection ## Description * As a Senior Data Engineer, you will architect and implement data pipelines and structure petabytes of data essential for making data-informed business decisions across different teams in Nordeus * In this role, you'll collaborate with top experts, work with rich datasets, and leverage cutting-edge technology, while seeing the direct impact of your work on products and players alike, * Build large-scale data pipelines that process billions of events every day with data processing frameworks like Airflow, Kafka, BigQuery and Google Cloud Platform * Design and develop our self-service Data Warehouse and Business Intelligence platform tools that enables our game teams to utilize data to bring the best experience to our players * Design and develop ML pipelines to help our data scientists efficiently develop new ML models using our game data Use best practices in continuous integration and delivery * Design and implement a robust and scalable data lake leveraging proven methodologies for optimal performance Design data models for efficient data storage and rapid retrieval * Manage the secure and efficient sourcing of external data from a diverse partner network * Help drive optimization, testing and tooling to improve data quality * Optimize existing pipelines and maintain all game-agnostic related data pipelines WHO YOU'LL WORK WITH: * You will work with other data engineers and different teams across Nordeus including Data Scientists, Business Analysts, Performance Marketing and Product teams ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Making Data Warehouses fast. 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