Data Engineer I — Remote Data Pipeline & Warehouse

United States Digital Space LLC; United States; Remote; USD 90,000 - 130,000; Full time

Job summary

The organization seeks an experienced Data Engineer to build and optimize our data warehouse and pipelines. You will collaborate with data scientists, analysts and software engineers to deploy data products that reveal insights and enable prescriptive actions.

The role emphasizes building scalable ETL/ELT processes, governance of metadata, and ensuring data quality while supporting disaster recovery and compliance initiatives.

Qualifications

• Requires 2 years of responsible experience in a data engineering, database administration, or data science role.
• Experience with relational databases (Postgres, Oracle, SQLServer) is required.
• Experience with data warehouses (Redshift, Snowflake, Incorta) is required.
• Proficiency with core programming languages (SQL, Python, C#) and Linux/Unix scripting is required.

Responsibilities

• Build, maintain and improve the enterprise data warehouse with focus on performance, patching and uptime.
• Collaborate with data analysts, data scientists and engineers to refine data models and pipelines.
• Establish and improve metadata management tools and processes.
• Develop and maintain ETL/ELT infrastructure across diverse data sources.
• Create and optimize data pipeline architecture for scalable analytics.
• Assemble large, complex data sets to meet business requirements.
• Ensure data quality, accuracy and timeliness through standards and tooling.
• Assist with disaster recovery planning to protect data assets.
• Complete required regulatory and compliance trainings.

Skills

SQL

Python

Data modeling

ETL/ELT

Data architecture

Linux/Unix

Communication

Education

Bachelors Degree in Computer Science / related quantitative field

Tools

SSIS

PostgreSQL

Oracle

Snowflake

Redshift

Job description

The organization seeks an experienced Data Engineer to build and optimize our data warehouse and pipelines. You will collaborate with data scientists, analysts and software engineers to deploy data products that reveal insights and enable prescriptive actions.

The role emphasizes building scalable ETL/ELT processes, governance of metadata, and ensuring data quality while supporting disaster recovery and compliance initiatives.