Data Engineer

Quantum Technologies. LLC; Los Angeles (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

Quantum Technologies. LLC is seeking a senior data engineer to design and build cloud-native data pipelines and architectures in our investment data platform. This role is based in Los Angeles and requires hands-on delivery across data modeling, warehousing, and orchestration.

You will need 7+ years of experience, expert SQL, Snowflake, and strong Python skills. Experience with AWS services and IaC (Terraform/CDK) plus CI/CD is essential; Private Credit experience is preferred.

Qualifications

• 7+ years of data engineering experience with cloud-native pipelines.
• Experience in the investment domain, Private Credit preferred.
• Expert SQL with large-scale data processing and automation.
• Deep data modeling, warehousing, and architecture knowledge.
• Snowflake expertise for cloud data warehousing and processing.
• AWS infrastructure skills: S3, ECR, Fargate, Glue, Lambda, EC2, Athena.
• Terraform/CDK for IaC, CI/CD practices.

Responsibilities

• Design, build, and optimize scalable, cloud-native data pipelines.
• Develop data architectures and warehousing models for analytics.
• Lead data modeling and integration across systems.
• Collaborate on data governance, quality, and automation initiatives.

Skills

SQL

Snowflake

Python

Data modeling

Data warehousing

Cloud data pipelines

Terraform/CDK

CI/CD practices

AWS services

Private Credit experience

Tools

Snowflake

AWS Cloud

ETL/Orchestration tooling

CI/CD tooling

Job description

J ob D escription:

• 7+ years of experience in data engineering, with a proven track record of designing, building, and optimizing scalable, cloud-native data pipelines and architectures.
• Experience in the investment domain, specifically Private Credit, is required.
• Expert-level proficiency in SQL, with strong experience in large-scale data processing, transformation, automation, and orchestration.
• Deep expertise in database design, data modeling, data warehousing, and data architecture best practices.
• Strong hands-on expertise in Snowflake for building and optimizing cloud-based data warehousing and processing solutions.
• Strong hands-on experience setting up AWS infrastructure, including Amazon S3, Amazon ECR, and AWS Fargate, with advanced proficiency in related services such as AWS Glue, AWS Lambda, Amazon EC2, and Amazon Athena.
• Private Credit experience is preferred.

Data Engineering Assessment Areas:

• Advanced SQL and query optimization
• Snowflake architecture and implementation
• Understanding of AWS Data Engineering responsibilities versus AWS Infrastructure responsibilities
• Strong Python proficiency
• Data Warehousing and Data Modeling concepts
• CI/CD and Infrastructure-as-Code practices (Terraform/CDK)
• API integrations and data processing use cases

Candidate Experience Expectations:

• Work independently with minimal supervisionTake end-to-end ownership of deliverables
• Demonstrate clear implementation experience across projects
• Articulate technical decisions, architecture, and hands-on contributions confidently

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.