5 years
0 Lacs
Posted:1 week ago|
Platform:
On-site
Full Time
We are scaling an AI/ML enabled Enterprise SAAS solution to help manage cash performance of large enterprises, including multiple Fortune-500 companies. You would be owning the architecture responsibility during the 1-10 journey of the product in the FinTech AI space.
Collaborate with data scientists and ML engineers to prepare data for AI/ML models and implement data-driven features
Implement data quality checks, monitoring, and alerting to ensure data accuracy and reliability
Optimize query performance across various database systems through indexing, partitioning, and query refactoring Develop and maintain documentation for data models, pipelines, and processes
Collaborate with cross-functional teams to understand data requirements and deliver solutions that meet business needs
Stay current with emerging technologies and best practices in data engineering
Ability to perform independent research to understand the product requirements and customer needs
Communicates effectively with the project teams and other stakeholders. Translate technical details to non-technical audience.
Expert at creating architectural artifacts for Data Warehouse.
Team, effort management.
Ability to set expectations for the client and the team. Ensure all deliverables are delivered in time at highest quality.
Solid understanding of data modeling principles and best practices for both operational and analytical systems
Proven ability to optimize database performance, including query optimization, indexing strategies, and database tuning
Experience with AWS data services such as RDS, Redshift, S3, Glue, Kinesis, and ELK stack
Proficiency in at least one programming language (Python, Node.js, Java)
Experience with version control systems (Git) and CI/CD pipelines
Accedepro Private Limited
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