About the Role
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.
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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.