[Remote] Senior ML/Data Engineer

Note: The job is a remote job and is open to candidates in USA. Insight Global is seeking a Senior Machine Learning / Data Engineer to join a financial services client’s AI Product team. The role focuses on building and productionizing machine learning solutions, developing scalable data products, and enabling AI-driven business outcomes through data architecture and engineering practices.

Responsibilities

• Design, build, and maintain scalable data pipelines and data products that support machine learning and AI initiatives
• Productionize machine learning models and partner closely with Data Scientists to deploy, monitor, and optimize models in production environments
• Develop and manage robust ELT/ETL processes using Python, DBT, and Snowflake
• Design and implement dimensional models, semantic layers, and scalable data warehouse solutions to support analytics and AI use cases
• Build data quality, governance, lineage, and monitoring capabilities to ensure reliable and trusted data assets
• Create and optimize datasets for machine learning training, inference, feature engineering, and model evaluation
• Collaborate with Data Science, Product, and Business stakeholders to identify opportunities for new AI-driven products and solutions
• Drive performance improvements and innovation across existing data platforms and machine learning workflows
• Own projects end-to-end with minimal oversight while maintaining high standards for delivery, scalability, and reliability
• Contribute to the continuous improvement of data architecture, engineering practices, and AI enablement across the organization

Skills

• 8+ years of experience in Data Engineering, Machine Learning Engineering, or related fields (5-6 years considered for exceptional candidates)
• Strong Python development experience for data engineering, machine learning, and automation
• Hands-on experience productionizing machine learning models and supporting AI solutions in enterprise environments
• Advanced SQL skills and extensive Snowflake experience (required)
• Strong DBT experience, including data transformations, testing, documentation, and model governance (required)
• Deep expertise in data warehousing, dimensional modeling, and building scalable data products
• Experience designing and maintaining complex ELT/ETL pipelines
• Strong understanding of data quality, observability, and governance best practices
• Ability to work independently, solve complex problems, and deliver results with minimal direction
• Proven track record of meeting deadlines, driving initiatives forward, and taking ownership of outcomes
• Experience with cloud platforms such as GCP or AWS
• Familiarity with MLOps concepts, model monitoring, feature stores, and model lifecycle management
• Experience working with modern orchestration tools such as Airflow or Cloud Composer
• Exposure to large-scale AI, machine learning, or advanced analytics environments
• Background building new data products or data platforms from the ground up

Company Overview

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