Analytics Engineering Architect * Expertise in Spark, PySpark, SQL, Python. * Experience with orchestration tools like Airflow, dbt. * Knowledge of data warehousing and lakehouse architecture. * Understanding of ML lifecycle and integration. * Strong focus on data quality and observability. * Experience with vector databases and real-time engineering. * Graph databases and graph analytics exposure. * DevOps experience with Docker, Kubernetes, Terraform. Roles & Responsibilities * Analytics Engineering Architect to design and orchestrate Analytics, data pipelines, and analytics platforms in BFSI. The Analytics Engineering Architect will be responsible for building machine learning and data backbone that supports advanced analytics, machine learning, and decision intelligence. You will architect and implement scalable data solutions using modern data engineering tools and cloud platforms. You will collaborate across departments to transform raw data into well-modeled, trusted data assets and ensure performance, reliability, and governance of the analytics infrastructure. This role is vital in operationalizing data-driven insights that influence strategic decisions in BFSI * Architect data and ML pipelines and analytical layers to support AI/ML and BI. * Build and manage data products and platforms. * Design cloud-native data architectures (AWS, GCP, Azure). * Own lifecycle of analytic data assets. * Design metadata, lineage, and governance layers. * Develop feature stores and monitoring tools. * Implement CI/CD and testing frameworks. Salary Range- $120,000-$200,000 a year #LI-SP3 #LI-VX1