Senior Data Warehouse Engineer

Team: IT

Location: Brazil

Commitment: Full-time

Workplace Type: remote

Accountabilities:

• Architect, build, and maintain scalable, high-performance data warehouse solutions that support analytics and operational needs.
• Develop reliable, well-documented data pipelines and ELT processes while maintaining strong standards for data quality and consistency.
• Optimize data warehouse performance through query optimization, partitioning, indexing, and other performance-tuning techniques.
• Partner with data analysts and data scientists to transform raw data into actionable analytics and support machine learning initiatives.
• Monitor, troubleshoot, and continuously improve data warehouse infrastructure while balancing performance, reliability, and cost efficiency.
• Establish and promote best practices for clean, well-structured, reliable, and accessible data.
• Work with modern cloud-based data warehouses such as ClickHouse and integrate data platforms with other cloud services.
• Contribute to developer-facing data tools and solutions that empower engineering and other technical teams.
• Support data transformation and modeling initiatives using tools such as dbt and SQL.
• Contribute to automation, testing, version control, code reviews, and other software engineering practices across data systems.
• Help improve the scalability, maintainability, and operational efficiency of the overall data platform.

Requirements:

• 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.

Benefits:

• Fully remote work arrangement within eligible hiring locations.
• Opportunity to work on large-scale data infrastructure supporting a technology platform focused on online security and fraud detection.
• Exposure to a modern technology stack including ClickHouse, Redshift, Confluent Kafka, dbt, Prefect, AWS, Terraform, Apache Superset, and Sigma.
• Opportunity to collaborate with data scientists, analysts, engineers, and globally distributed technical teams.
• High level of ownership and autonomy in a data engineering environment.
• Opportunity to contribute to developer-facing tools and scalable data platform initiatives.
• US-based compensation range of $152,000–$205,000; compensation may vary by hiring location and is not directly applicable to all locations.
• Fully remote international environment with team members distributed across multiple countries and time zones.
• Visa sponsorship is not provided; candidates must be authorized to work from their home location.
• Specific India-based salary, healthcare, retirement, paid time off, and other benefits were not specified in the source description.