Data & ML Engineer

Next Ventures; Fort Lauderdale (FL); Hybrid; USD 120,000 - 150,000; Full time

Job summary

A leading Ecommerce Retail Business in Fort Lauderdale is seeking a Data & ML Engineer to design and scale their data platform and ML ecosystem. Collaborating closely with the VP of Machine Learning, you will drive the design and deployment of models that enable business intelligence and predictive analytics. This hybrid role offers significant growth opportunities as the company expands its AI initiatives.

Qualifications

• 5+ years in data engineering or ML engineering.
• Demonstrated experience in building and scaling data platforms.
• Experience deploying and maintaining ML models in production with MLOps best practices.

Responsibilities

• Architect and build the enterprise lakehouse across Microsoft Fabric, Snowflake, Databricks, or AWS.
• Ensure data governance, quality, and security are embedded throughout the architecture.
• Partner closely with the VP, to translate business challenges into data/BI or AI/ML solutions.
• Contribute to the end-to-end development of machine learning models.

Skills

Data engineering

Machine learning engineering

MLOps

Data governance

Data modeling

Tools

Azure ML

Databricks

Snowflake

Microsoft Fabric

MLflow

Kubeflow

Job description

Overview

I am partnered with a Ecommerce Retail Business based our of Fort Lauderdale, who are looking to hire a critical technical role for the business.

This Data & ML Engineer would be responsible for designing, building, and scaling the companies next-generation data platform and ML ecosystem. You will work as the right hand to the VP, Machine Learning and help in architecting the foundation of their cloud lakehouse and drive the hands-on design, development, and deployment of scalable models and data pipelines that power business intelligence, personalization, and predictive analytics across the organization.

This role offers huge growth, but also the chance to be able to come in and join a company where you can be at the forefront of them scaling their AI initiatives.

The team work on a hybrid model meaning you will be in the office on Tuesdays and Thursdays.

Responsibilities

• Architect and build the enterprise lakehouse across Microsoft Fabric, Snowflake, Databricks, or AWS
• Ensure data governance, quality, and security are embedded throughout the architecture
• Partner closely with the VP, to translate business challenges into data/BI or AI/ML solutions
• Contribute to the end-to-end development of machine learning models and supporting use cases across retail and eCommerce
• Build reusable MLOps pipelines

Qualifications

• 5+ years in data engineering or ML engineering
• Demonstrated experience in building and scaling data platforms
• Experience deploying and maintaining ML models in production with MLOps best practices
• Familiarity with MLOps platforms such as Azure ML, MLflow, Kubeflow, or Databricks
• Solid understanding of data modeling, ELT/ETL patterns, streaming, and orchestration (ADF, Airflow, Fabric Data Pipelines)