Job Description
Provide strategic recommendations on leveraging data lakes, data meshes, and serverless architectures to optimize data processing and storage
Assess and recommend AI/ML-enabled data architectures that facilitate scalable feature engineering and model training pipelines
Define and advise on the design of modern, future-ready data architectures that align with business goals and support AI, analytics, and automation
Provide thought leadership on best practices for data modeling, data warehousing, and lakehouse architectures to ensure scalability and performance
Develop data models, schemas, and standards that ensure data integrity, quality, and accessibility
Design & Build solutions with AI Services like Bedrock, Google etc.
Mentor and guide team members in best practices for data architecture and management
Participate in code reviews and contribute to the improvement of data engineering best practices
Job Requirements
Bachelor's degree in Computer Science, Engineering, or a related field
4-5 years of experience in designing and building high-performance cloud-based data architectures
Experience in Data Engagements, especially leading data strategy, roadmap and implementation
Tech Stack – Python, SQL, AWS, Snowflake, DBT, Airflow, Bedrock, NoSQL
Knowledge of container-based big data architectures and Kubernetes
Familiarity with DevOps / DataOps / MLOps concepts
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