AI/ML Software Engineer shaping AI strategy and building scalable AI/ML components. Developing solutions atop Smile Digital Health’s FHIR - based healthcare data platform.
About the role
- Data AI Engineering Specialist building and maintaining data infrastructure for Data AI platforms at Morgan Stanley. Collaborating with stakeholders and handling data pipelines and governance standards.
Responsibilities
- Develop and maintain data pipelines and ETL (Extract, Transform, Load) processes
- Work with structured and unstructured data to ensure it is accessible and usable
- Optimize data systems for performance and scalability
- Implement data quality and data governance standards
- Collaborate with stakeholders across technology and business units to understand their data needs and translate them into technical solutions and provide data-driven insights
- Contribute to the documentation and knowledge sharing within the team, creating, and maintaining technical documentation and training materials
- Participate in code reviews and contribute to the improvement of development processes
- Contribute to the broader data architecture community through knowledge sharing, presentations
Requirements
- 8 years+ of being a practitioner in data engineering or a related field
- Proficiency in programming skills in Python
- Experience with data processing frameworks like Apache Spark or Hadoop
- Knowledge of database systems (SQL and NoSQL)
- Experience working on Snowflake and Databricks
- Experience on Snowflake Cortex will be really appreciated
- Familiarity with cloud platforms (AWS, Azure) and their data services
- Understanding of data modeling and data architecture principles
- Experience with data warehousing concepts and technologies
- Experience with message queues and streaming platforms (e.g., Kafka)
- Experience with version control systems (e.g., Git)
- Experience using Jupyter notebooks for data exploration, analysis, and visualization
- Excellent communication and collaboration skills
- Ability to work independently and as part of a geographically distributed team.
Benefits
- health insurance
- retirement plans
- paid time off
- flexible work arrangements
- professional development
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