AWS Data Engineer - Data Lakehouse & Pipelines (Healthcare)

MACHINE LEARNING TECHNOLOGIES LLC; Seattle (WA); On-site; USD 140,000 - 180,000; Part time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC is seeking an AWS Data Engineer in Seattle to build and operate scalable data extraction, ingestion, and processing pipelines for large healthcare datasets. The role emphasizes modern architectures like Data Mesh and Lakehouse, with emphasis on data governance and cloud security.

You will implement automated data flows, integrate API interfaces, and support analytics capabilities while aligning with privacy and security standards.

Qualifications

• Experience with data concepts (SQL, NoSQL, Normalization) and advanced data structures.
• IaC tools such as CloudFormation and Terraform.
• Experience designing cloud data solutions across AWS technologies (EC2, EMR, DMS, GLUE, S3, Redshift, etc.).
• MDM implementations with platforms like Reltio, Informatica.

Responsibilities

• Build and operate distributed data extraction, ingestion, and processing systems for large data sets.
• Apply modern data architectures (Data Mesh, Data Lakehouse) in practice.
• Leverage MDM (Reltio) for master data governance and quality.
• Develop and implement API interfaces for data accessibility.
• Create secure cloud data solutions aligning with privacy and security controls.
• Enable data analytics capabilities and ensure requirements meet standards.

Skills

Data engineering

SQL

NoSQL

Terraform

CloudFormation

AWS data solutions

MDM (Reltio/Informatica)

Python/Scala/Go/C#

Bash/PowerShell

Data Lake/Data Warehouse/ETL/ELT

Data governance/BI

Tools

CloudFormation

Terraform

Job description

MACHINE LEARNING TECHNOLOGIES LLC is seeking an AWS Data Engineer in Seattle to build and operate scalable data extraction, ingestion, and processing pipelines for large healthcare datasets. The role emphasizes modern architectures like Data Mesh and Lakehouse, with emphasis on data governance and cloud security.

You will implement automated data flows, integrate API interfaces, and support analytics capabilities while aligning with privacy and security standards.