Data AI Engineering Specialist (Hybrid)
Montreal 700, Canada
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Morgan Stanley
Discover how we help individuals, families, institutions and governments raise, manage and distribute the capital they need to achieve their goals.- 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.
- 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.
- Familiarity with data visualization tools (e.g., Tableau, Power BI).
- Familiarity with data governance and security best practices (e.g., data access control, data masking).
- Experience with Agile methodologies.
- Familiarity with data catalog and metadata management tools (e.g., Collibra).
- Familiarity with CI/CD pipelines and DevOps practices.
WHAT YOU CAN EXPECT FROM MORGAN STANLEY:
We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 89 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - arenāt just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, youāll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. Thereās also ample opportunity to move about the business for those who show passion and grit in their work.
To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-officesā into your browser.
Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index š°
Tags: Agile Architecture AWS Azure CI/CD Databricks Data governance Data pipelines Data quality Data visualization Data Warehousing DevOps Engineering ETL Git Hadoop Jupyter Kafka Machine Learning NoSQL Pipelines Power BI Python Security Snowflake Spark SQL Streaming Tableau Unstructured data
Perks/benefits: Career development
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