Lead Data AI Engineer_Vice President_Data & Analytics Engineering
Morgan Stanley (company site, opens in a new tab)10+ yrsBengaluruOn-siteDirect career pageEst. 30–50 LPA
Posted 12h ago
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Job description
Structured overview of role & requirements
About This Role
- Develop and maintain scalable data pipelines, ETL processes, and ensure data quality and governance across structured and unstructured data.
- Collaborate with business and technology stakeholders to translate data needs into technical solutions and contribute to data-driven insights.
- Lead knowledge sharing through documentation, code reviews, training materials, and participation in the broader data architecture community.
Minimum Requirements
- 10+ years of experience in data engineering or a related field, with at least 6 years relevant to the role.
- Graduate degree in Computer Science, Information Systems, or equivalent.
- Proficiency in Python and experience with Apache Spark or Hadoop, Snowflake or Databricks, and familiarity with cloud platforms like AWS or Azure.
- Experience with data modeling, data warehousing, message queues/streaming platforms (e.g., Kafka), and version control systems (e.g., Git).
Ideal Candidate Profile
- Experienced senior data engineer capable of independently owning and evolving enterprise-grade data infrastructures and pipelines.
- Strong background with both cloud-based data platforms (Snowflake/Databricks) and big data frameworks, with understanding of data architecture principles.
- Able to collaborate across distributed teams and stakeholders while contributing to the wider data architecture community and technical leadership at VP level.