Azure Data & ML Engineer - ETL, Databricks & MLOps

Ethereum Technologies; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Ethereum Technologies is seeking an experienced Data & ML Engineer to design, develop, and implement scalable data pipelines and ML solutions in an Azure cloud environment. You will collaborate with engineering and data science teams to deliver secure, production-ready systems.

The role emphasizes building robust ETL/ELT pipelines, deploying models with CI/CD, and operating in a modern data lake/Data Factory ecosystem. Strong Azure experience is required.

Qualifications

• Hands-on experience as a Data Engineer, ML Engineer, or Cloud Platform Engineer.
• Strong experience with Microsoft Azure data engineering services.
• Proficiency in Python, SQL, and/or Scala.
• Experience developing and supporting production-grade data pipelines.
• Experience with Spark, Databricks, or comparable big data processing frameworks.
• Familiarity with CI/CD pipelines, DevOps, and MLOps practices.

Responsibilities

• Design, develop, and maintain scalable data ingestion, transformation, and ETL/ELT pipelines.
• Build and optimize Azure-based data platforms using Databricks, Data Lake, Synapse, and related technologies.
• Support deployment and operationalization of machine learning models through CI/CD and MLOps practices.
• Implement monitoring, logging, troubleshooting, and performance optimization for data and ML workloads.
• Collaborate with data scientists and engineering teams to translate requirements into production-ready solutions.
• Develop reusable, automated components following cloud engineering best practices.

Skills

Azure data engineering

Python

SQL

Spark/Databricks

CI/CD/MLOps

Communication

Tools

Docker

Kubernetes

Azure Data Factory

Synapse

Job description

Ethereum Technologies is seeking an experienced Data & ML Engineer to design, develop, and implement scalable data pipelines and ML solutions in an Azure cloud environment. You will collaborate with engineering and data science teams to deliver secure, production-ready systems.

The role emphasizes building robust ETL/ELT pipelines, deploying models with CI/CD, and operating in a modern data lake/Data Factory ecosystem. Strong Azure experience is required.