Senior Data Engineer: Cloud Data & ML Pipelines

Capital One; North Dakota; Vor Ort; USD 197.000 - 225.000; Vollzeit

Zusammenfassung

Capital One is seeking an experienced Data Engineer 4 to drive cloud-first data solutions. The role focuses on designing, building, and delivering scalable data pipelines, collaborating with Agile teams, and mentoring others in modern data platforms.

The ideal candidate has 4+ years in data engineering, strong Python/SQL skills, and hands-on experience with Databricks and Snowflake in a distributed data environment.

Qualifikationen

• Bachelor's degree or higher in CS or a related quantitative field.
• At least 4 years of application development experience.
• At least 2 years in distributed data.
• At least 2 years of SQL experience.
• At least 2 years in one programming language (Python, Java, or Scala).
• At least 2 years in data pipeline design and development.
• At least 1 year in data modelling and end-to-end data solutions.

Aufgaben

• Collaborate with Agile teams to design, develop, test, and support data solutions.
• Influence developers, data analysts and data scientists across ML and lakehouse architecture.
• Utilize Python, Spark, and cloud data warehousing platforms (Databricks, Snowflake).
• Build scalable cloud data solutions with a focus on performance and security.
• Architect data engineering patterns for quality, maintainability, and reuse.
• Communicate complex data concepts to stakeholders to drive alignment.

Kenntnisse

Python

SQL

Spark

NoSQL

Ausbildung

Bachelor's Degree in CS or related field

Tools

Databricks

Snowflake

EMR

Airflow

Dagster

MongoDB

Cassandra

DynamoDB

Redshift

Jobbeschreibung

Capital One is seeking an experienced Data Engineer 4 to drive cloud-first data solutions. The role focuses on designing, building, and delivering scalable data pipelines, collaborating with Agile teams, and mentoring others in modern data platforms.

The ideal candidate has 4+ years in data engineering, strong Python/SQL skills, and hands-on experience with Databricks and Snowflake in a distributed data environment.