Data Engineer

Remote (United States)

Compensation

Base salary range: $150,000 - $180,000 per year, based on experience and qualifications.

Employment Type

Full-Time

About the Role

This opportunity is for a Data Engineer responsible for building and maintaining the data pipelines, storage systems, and processing workflows that support reporting, analytics, and downstream applications across multiple projects.

In this role, you will collaborate with Product Management and Engineering teams to define data requirements and pipeline architecture. You will help ensure data solutions remain reliable, scalable, and accessible for both batch and real-time use cases while contributing to the evolution of the broader data architecture as data volumes, sources, and analytics requirements grow.

What You’ll Do

• Design, build, and maintain ETL and ELT data pipelines that extract, transform, and load information from source systems into target data stores.
• Partner with Product Management and downstream teams to define data requirements and establish clear data quality expectations.
• Collaborate with Engineering teams to define pipeline architecture for both batch and real-time data processing.
• Write and optimize SQL queries and scripts using Python or similar technologies to support data transformation and validation.
• Monitor pipeline health, investigate and resolve failures, and help ensure reliable and timely data availability.
• Support the integration of new data sources into cloud-based data warehouses and data lakes.
• Help shape future data architecture to accommodate higher data volumes, additional data sources, and expanding analytics use cases.
• Document data flows, schemas, and pipeline logic so technical teams and stakeholders have clear and reliable reference materials.

Qualifications

• Associate's degree or equivalent professional experience.
• 2+ years of technical IT experience, including exposure to data pipeline development, SQL, or scripting.
• Ability to obtain and maintain a U.S. Government Public Trust or Security Clearance.
• Experience with data pipeline orchestration tools such as Airflow, dbt, or similar technologies.
• Familiarity with distributed data processing frameworks such as Spark or Kafka.
• Experience working with cloud data warehouses or data lakes, including Snowflake, BigQuery, Redshift, S3-based architectures, or similar platforms.
• Proficiency in Python for data engineering tasks.
• Understanding of data modeling principles and data quality best practices.