Senior Data Engineer

Harnham; California; On-site; USD 120,000 - 160,000; Full time

Job summary

A leading data solutions company is seeking a Senior Data Engineer to build and develop scalable data pipelines and transformation frameworks. The ideal candidate has over 5 years of experience in data engineering, strong programming skills in Python, and hands-on experience with large-scale data platforms like AWS or Azure. This high-impact position requires a strong focus on data security and reliability, as well as the ability to work independently in a fast-paced environment.

Qualifications

• 5+ years of experience in data engineering or backend engineering.
• Strong programming skills in Python or a comparable language.
• Hands on experience with Spark, PySpark, SQL, and dbt.
• Experience with large scale data platforms in AWS, Azure, or GCP.
• Familiarity with containerization and modern deployment practices.
• Ability to work autonomously in fast moving environments.

Responsibilities

• Design and build scalable data pipelines for high volume data processing.
• Own data ingestion and egress systems that integrate multiple operational data sources.
• Develop secure, reliable data models for internal data products.
• Partner with teams to translate business needs into production grade systems.
• Implement best practices across data modeling, testing, and security.
• Debug, monitor, and optimize transformation pipelines in production.

Skills

Data engineering

Python

Spark

SQL

dbt

Containerization

Data security

Tools

AWS

Azure

GCP

Job description

The Role

As a Senior Data Engineer you will help build and evolve the systems that power internal data products and operational insights.

Key responsibilities include:

• Design and build scalable data pipelines and transformation frameworks for high volume data processing
• Own data ingestion and egress systems that integrate multiple operational data sources
• Develop secure, reliable data models that power internal data products and applications
• Partner with engineering, product, and operations teams to translate business needs into production grade systems
• Implement and advocate for best practices across data modeling, testing, CI/CD, and security
• Debug, monitor, and optimize complex transformation pipelines in production environments

What They’re Looking For

• 5+ years of experience in data engineering or backend engineering
• Strong programming skills in Python or a comparable language
• Hands on experience with Spark, PySpark, SQL, and dbt
• Experience working with large scale data platforms in cloud environments such as AWS, Azure, or GCP
• Familiarity with containerization and modern deployment practices
• Ability to work autonomously in fast moving environments
• Strong ownership mindset and attention to data security and reliability
• Must be a U.S. Person due to export-controlled information requirements

This is a high-impact role focused on building durable data systems that directly support operational execution at scale.