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Machine Learning Data Engineer
HonorVet Technologies
- +2
- +7
- United States
- +2
- +7
- United States
About
Only W2 Overview: Our client in the commercial banking domain is hiring two Machine Learning Data Engineers to support a high-impact initiative within the Data Quality Team. One role will focus on solution architecture, requiring experience implementing a full machine learning framework. The second will be more of an Engineer/Business Analyst hybrid, supporting the lead architect and contributing to model development and automation efforts.
These roles are part of a strategic effort to automate the review of over 25,000 data quality rules currently being manually aggregated and analyzed. The goal is to build and implement a prototype ML model by year-end, so candidates must be available for a fast-paced delivery timeline (no extended time off planned in December).
Project Scope:
Automate the rule review process currently handled manually using Informatica IDQ, with a transition toward Snowflake. Develop and deploy a Machine Learning model to analyze rule pass/fail outcomes. Improve efficiency by reducing manual resource dependency through intelligent automation.
Responsibilities:
Follow the company's software development lifecycle to design, code, configure, test, debug, and document system and application programs. Prepare technical design specifications based on functional requirements and analysis documents. Participate in architecture, design, and code reviews. Collaborate with development staff to ensure quality and consistency. Develop and maintain operational and system-level documentation. Build and implement a prototype ML model with a quick turnaround. Support scalable API integrations between internal and external systems (nice to have).
Core Requirements:
Strong command of SQL and experience with relational databases (e.g., PostgreSQL, MySQL, Oracle, Snowflake). Proficient in Python and/or R for data analysis and model development. Experience with ML/AI programming and modern machine learning standards. Hands-on experience with cloud platforms (AWS, Azure, GCP) and services like Lambda, S3, Azure Functions, BigQuery. Familiarity with automation frameworks (e.g., Power Automate, Python scripting). Understanding of data quality, management, and governance concepts. Experience with Web Application Server enhancements and infrastructure standards.
Preferred Qualifications (Nice-to-Haves):
Experience with Informatica IDQ. Familiarity with Snowflake ML libraries or programming extensions. Background in designing and implementing scalable API integrations.
Soft Skills:
Highly motivated, proactive, and collaborative team player. Able to work independently and meet tight deadlines. Strong communication and problem-solving skills.
Nice-to-have skills
- Machine Learning
- MySQL
- Oracle
- PostgreSQL
- Python
- R
- SQL
Work experience
- Data Engineer
- Machine Learning
Languages
- English
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