Full-Time Senior Data/ML Engineer

ESSENTIAL DUTIES AND RESPONSIBILITIES

• Participate in Data and ML discovery activity to understand feasibility of new ML use cases
• Work on use case feasibility discussions and translate business ideas / needs to user stories
• Lead exploratory data analysis for various use cases to ensure robust ML implementations that can provide reliable predictions
• Work with business users and other subject matter experts to implement Data & ML solutions
  • Understand business problems/needs and propose solutions.
  • Design or suggest improvements to optimize existing solutions
  • Implement and test the solution to ensure results or predictions meet the business criteria
  • Deploy and enhance the solutions
  • Operationalize Data & ML Solutions
• Develop and maintain complex Data, ML Pipelines and Models
  • Build and enhance Data and ML Pipelines to ingest data and build data features for modeling
  • Develop and maintain CICD artifacts to support Data and ML Solutions
  • Monitor and troubleshoot processes daily
  • Document new and existing processes
• Support and maintain Data & ML solutions
  • Troubleshot and resolve production issues
  • Implement enhancements and bug fixes
  • Optimize ML pipelines, ML Models and Business predictions
  • Proactively and independently identify performance issues and recommend enhancements
  • Proactively monitor and support production systems, Data and ML solutions including on-call responsibilities
• Work collaboratively with other Data Engineers to understand and contribute to the overall data architecture and pipelines
• Mentor and assist other team members on issues and methodology
• Develop software with a security-first mindset using knowledge of standard security protocols and common security risks, secure coding techniques, and appropriate usage and protection of sensitive information such as PHI. Identify potential security issues during requirements analysis, development, and threat modeling discussions.

KNOWLEDGE & REQUIREMENTS

• Experience with Data Engineering, Modeling and Data Warehousing technologies
• Experience with ML Engineering, Modeling and operationalizing ML Models
• Strong experience in ETL design, development, testing, maintenance, and implementation of data pipelines and analytics initiatives
• Strong SQL programming/python scripting/data analysis experience
• Develops ETL mapping specifications for loading information into the data warehouse and for ensuring reliability of information loaded.
• Experience in gathering requirements, development, testing and maintenance of Data and Analytics Solutions.
• Validate data to ensure accuracy and consistency and meets the requirements criteria
• Partners with business end-users to develop and implement collaborative solutions
• Knowledge with Qlik Replicate technologies is a plus
• Strong knowledge in AWS Cloud Data Services (AWS RedShift, Glue, SageMaker, and Bedrock)
• Experience using cloud services for concepts such as storage and compute. Capable of applying infrastructure as code practices.
• Provides a positive impact on team: influences team decisions, mentors peers, drives innovation
• Excellent written and verbal communication skills
• Experience with developing Chatbot automations is a plus

DESIRABLE QUALIFICATIONS

• Self-motivated, quick learner, and thrives in fast-paced environments while adapting seamlessly to new technologies
• Experience working with healthcare technology.
• Experience working with PHI data and HIPAA standards.
• Experience resolving issues that do not have clear answers.
• High sense of urgency and accountability
• Adaptable, friendly, and ability to work with teams.
• Passion for data and digging into the minutia of datasets.

EDUCATION & EXPERIENCE REQUIREMENTS

• Minimum years of work experience: 7 years
• Minimum level of education or education/experience: Bachelors or equivalent work experience in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, IT
• 3 years of Data Warehousing experience
• 4 years of experience in build data and ML pipelines, and complex SQL scripting
• 5 years of experience in Data Engineering