Senior Data Warehouse Engineer

This role offers the opportunity to shape the data infrastructure supporting a high-growth technology platform focused on online security and fraud detection. You will design and optimize scalable data warehouses, reliable pipelines, and modern ELT processes that enable analytics and data-driven decision-making. Working closely with data scientists, analysts, and engineers, you will transform complex data into trusted and actionable insights. The position combines hands-on engineering with opportunities to improve performance, reliability, cost efficiency, and developer productivity. You will work with modern cloud technologies including ClickHouse, Redshift, AWS, Kafka, dbt, and Prefect. This is a strong opportunity for an autonomous data engineer who enjoys solving complex problems in a globally distributed, fully remote environment.

• Extensive professional experience designing, implementing, and optimizing data warehouses in cloud environments such as AWS or GCP.
• Strong hands-on expertise with data modeling and transformation tools, particularly dbt.
• Excellent SQL skills and experience with modern columnar or cloud data warehouse technologies such as ClickHouse, Databricks, BigQuery, Snowflake, or Redshift.
• Experience developing and managing data pipelines using orchestration tools such as Prefect or Airflow.
• Solid understanding of data engineering principles, warehouse architecture, transformation, and data quality.
• Strong software engineering fundamentals, including version control, code reviews, testing, automation, and maintainable development practices.
• Experience working collaboratively with data scientists, analysts, engineers, and other cross-functional stakeholders.
• Strong English communication skills for effective collaboration within a globally distributed remote team.
• High degree of ownership, autonomy, and accountability, with the ability to work effectively in ambiguous environments.
• Strong analytical and problem-solving skills, with a practical approach to troubleshooting and performance optimization.
• Familiarity with business intelligence and visualization tools such as Apache Superset, Sigma, Tableau, or Looker is a plus.
• Experience with infrastructure-as-code tools such as Terraform and a DevOps-oriented mindset is desirable.
• Scripting or automation experience with Bash, Python, or Go is an advantage.
• Experience with technologies such as Kafka, AWS, Terraform, and modern data visualization platforms is beneficial.