Remote Senior Data Engineer – Pipelines & ML Prep

The Consensus; United States; On-site; USD 120,000 - 150,000; Full time

Job summary

Stord is seeking an experienced Data Engineer to join our team. You will design, implement, and optimize data pipelines and help evolve our data warehouse to support analytics and ML initiatives.

You will work closely with data scientists, product managers, and engineers to ensure data quality and accessibility across the platform. You will contribute to building scalable data infrastructure on GCP, leverage tools like dbt and Airflow, and mentor teammates while promoting data-driven decision

Qualifications

• 5+ years of experience in data engineering or a related field.
• Proven experience building and maintaining data pipelines and data warehouses.
• Experience with cloud platforms, preferably GCP.
• Experience with SQL and data modeling.
• Experience with data transformation tools such as dbt, or similar.

Responsibilities

• Design, develop, and maintain scalable and reliable data pipelines using modern data engineering tools.
• Help drive the re-architecture of our data warehouse to improve performance, scalability, and data quality.
• Implement data cleansing, transformation, and validation processes to ensure data accuracy and consistency.
• Collaborate with other engineers and stakeholders to define data requirements and develop data models.
• Build and maintain data infrastructure on GCP, including data lakes, data warehouses, and data pipelines.

Skills

SQL

Python

dbt

Airflow

data modeling

BigQuery

Snowflake

Tools

Git

Job description

Stord is seeking an experienced Data Engineer to join our team. You will design, implement, and optimize data pipelines and help evolve our data warehouse to support analytics and ML initiatives.

You will work closely with data scientists, product managers, and engineers to ensure data quality and accessibility across the platform. You will contribute to building scalable data infrastructure on GCP, leverage tools like dbt and Airflow, and mentor teammates while promoting data-driven decision