Data Engineer

Machine Learning Technologies, LLC; Los Angeles (CA); On-site; USD 130,000 - 180,000; Full time

Job summary

Machine Learning Technologies, LLC seeks a senior data engineer in Los Angeles to lead building scalable, cloud-native data pipelines and architectures. You will design robust data models, optimize Snowflake-based solutions, and work with AWS services to support investment-focused data platforms.

The role requires 7+ years in data engineering, strong SQL, and hands-on Snowflake/AWS experience, with Private Credit experience preferred.

Qualifications

• 7+ years of experience in data engineering
• Experience in the investment domain, specifically Private Credit, is required
• Expert-level proficiency in SQL
• 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 S3, ECR, Fargate, and related services such as Glue, Lambda, EC2, Athena
• Private Credit experience is preferred

Responsibilities

• Own end-to-end data engineering deliverables.
• Design and optimize cloud-native data pipelines and architectures.
• Collaborate with teams to ensure scalable, reliable data solutions.

Skills

SQL

Snowflake

AWS

Python

Data warehousing

Data modeling

CI/CD

Terraform

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.