Data Engineer

Imprint

full-time

Posted on: 9/16/2025

Origin: • 🇺🇸 United States • California, New York, Washington

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💰 $170,000 - $220,000 per year

Mid-LevelSenior

AirflowCloudETLKafkaPythonSQL

About the role

Build and maintain scalable data pipelines and infrastructure across batch and streaming systems.
Support and improve core components of Imprint's data stack, including Snowflake, dbt Cloud, Change Data Capture frameworks, and reverse ETL integrations.
Implement data modeling best practices and contribute to testing, observability, and governance initiatives.
Collaborate with stakeholders across Product, Analytics, Finance, and Engineering to ensure timely and accurate data delivery.
Assist with external data integrations, such as partner-facing data shares (e.g., S3, SFTP, Snowflake) and financial reporting pipelines (e.g., with Netsuite).
Participate in design discussions for scaling data infrastructure, including schema design, orchestration, and data lineage.
Create clear documentation and ensure reproducibility for datasets and workflows you develop.
Learn about modern data tools and trends and suggest improvements to existing processes.

3+ years of experience in data engineering, analytics engineering, or related roles
Solid experience with Snowflake and dbt, with an understanding of dimensional modeling and data warehouse concepts
Hands-on experience with ETL/ELT pipelines and familiarity with orchestration frameworks (e.g., dbt Cloud, Airflow)
Working knowledge of data integration tools like Fivetran or similar Change Data Capture solutions
Strong SQL skills and proficiency in Python or a similar programming language
Experience building and maintaining production data systems with guidance from senior team members
A detail-oriented mindset and enthusiasm for building clean, maintainable data systems
Strong communication skills and ability to work effectively with cross-functional partners
Legally authorized to work in the United States (application requests authorization and visa sponsorship status)
Nice to have: Experience in fintech, high-growth startups, or customer-facing data products; familiarity with event streaming technologies like Kafka or Kinesis; exposure to data governance, security, or compliance practices; interest in ML pipelines or experimentation frameworks