Senior Data Warehouse Engineer

Fingerprint; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Fingerprint is a globally remote company seeking a Senior Data Warehouse Engineer to shape the data backbone powering its analytics platform.

You will architect scalable data warehouses on cloud platforms, build robust ELT pipelines with dbt, and collaborate with data scientists, analysts, and engineers to drive smarter decision-making and innovation.

Qualifications

• Experience designing data warehouses in cloud environments (AWS, GCP, etc.).
• Hands-on with data modeling and transformation tools like dbt.
• Excellent SQL skills and familiarity with columnar data warehouses.

Responsibilities

• Architect and build scalable, high-performance data warehouse solutions for analytics and operations.
• Develop and maintain reliable data pipelines and ELT processes with quality data.
• Continuously tune and optimize data warehouse performance—partitioning, indexing, and query optimization.

Skills

Team player

Ownership/autonomy

English communication

Cloud data warehouses

dbt

SQL

Tools

ClickHouse

Databricks

BigQuery

Snowflake

Job description

Fingerprint empowers enterprises to detect and stop online fraud with the world’s most accurate device intelligence. We lead our industry with bleeding-edge identification capabilities and work on turning new ideas and discoveries in the fraud detection space into reality. Our customers range from innovative startups to leading enterprise companies, including Plaid, Dropbox, and Booking.com.

Fingerprint is a globally dispersed, 100% remote company. We were named on on the 2026 Forbes Best Startup Employers list and ranked #803 on the 2026 Inc. 5000 list of America’s fastest-growing private companies.

We have raised $77M and are backed by Craft Ventures (Tesla, Facebook, Airbnb ), Nexus Venture Partners ( Postman, Apollo.io, MinIO, Druva) and Uncorrelated Ventures ( Redis, Rollbar, Gradle).

At Fingerprint, we’re redefining online security and identity verification through cutting-edge technology and data-driven insights. As a Senior Data Warehouse Engineer, you’ll play a key role in shaping the data backbone that powers our industry-leading platform.

We’re looking for a collaborative, self-starter with a passion for data engineering and a knack for building efficient, scalable data pipelines and warehouses. In this role, you’ll work closely with data scientists, analysts, and engineers to design and implement robust solutions that drive smarter decision-making and fuel innovation.

Responsibilities:

• Architect and build scalable, high-performance data warehouse solutions that empower analytics and operational excellence across our platform.
• Develop and maintain reliable, well-documented data pipelines and ELT processes, ensuring data quality and consistency.
• Continuously tune and optimize data warehouse performance—partitioning, indexing, and query optimization are your bread and butter.
• Partner with data analysts and scientists to transform raw data into insightful, actionable analytics and machine learning models.
• Troubleshoot, monitor, and refine our data warehouse infrastructure, balancing speed and cost efficiency.
• Foster a data-driven culture by sharing best practices and championing clean, well-structured data.
• Work with modern cloud-based data warehouses like ClickHouse and ensure seamless integration with our services.
• Contribute to the development of new developer-facing data tools that empower teams across the company.

Qualifications:

• A team player who loves collaborating in a tight-knit, cross-functional team.
• A high degree of ownership and autonomy, with a proven ability to thrive in ambiguous environments.
• Strong communication skills in English to navigate our global, remote team.
• Extensive experience designing, implementing, and optimizing data warehouses in cloud environments (AWS, GCP, etc.).
• Hands-on expertise with data modeling and transformation tools like dbt.
• Excellent SQL skills and familiarity with modern columnar storage data warehouses (e.g., ClickHouse, Databricks, BigQuery, or Snowflake).
• Experience with data p