data infrastructure.

JD-Data Platform & Architecture• Design and evolve cloud-native data lakes / warehouses (e.g., Snowflake, Databricks, BigQuery).• Establish scalable batch & streaming pipelines using Spark/Flink, Kafka, Airflow/Dagster, and dbt.• Implement robust data-quality, catalog, and governance frameworks (e.g., Great Expectations, Unity Catalog).MLOps & Model Lifecycle• Build automated CI/CD pipelines for ML (MLflow, Kubeflow, SageMaker, Vertex AI).• Set up feature

KEY RESPONSIBILITIES...● Build and operationalize cloud-based platform components● Develop production-quality data ingestion pipelines with automated quality checks using GCP andAstronomer● Assess existing systems architecture and recommend technical improvements● Develop Python-based automation to support product development and data analytics● Resolving technical problems as they arise● Research and propose emerging technologies and platform enhancements

 Should have a minimum 2+ years in Data Engineering, Data Analytics platform. Should have strong hands-on design and engineering background in AWS, across a wide range ofAWS services with the ability to demonstrate working on large engagements. Should be involved in Requirements Gathering and transforming them to into Functionally andtechnical design. Maintain and optimize the data infrastructure required for accurate extraction, transformation, andloa