Data Lakehouse Architect

We are looking for an experienced Data Lakehouse Architect with 10–15 years of experience, preferably within the Financial Services / Banking (FSI) domain, to lead enterprise-scale Lakehouse architecture and modernization initiatives. Responsibilities

• Own the end-to-end architecture and technical vision for the enterprise Lakehouse platform.

• Design data products, data marketplace, knowledge layers, and agentic AI workloads.

• Define target architecture with focus on scalability, security, reusability, and performance.

• Develop roadmaps, frameworks, and reusable architecture patterns for new data capabilities.

• Design solutions using Databricks, Snowflake, Cloudera, Azure, AWS, or GCP.

• Architect RAG, Vector DB, Graph DB, embeddings, and agentic AI workloads.

• Partner with business teams to define data contracts, SLAs, and data quality standards.

• Review technical/design specifications and ensure delivery follows enterprise standards.

• Lead performance engineering, optimization, continuous improvement, and production readiness.

• Collaborate with business, technology, vendors, and distributed engineering teams to deliver strategic solutions.

Requirements

• 10–15 years of experience in Data Architecture / Data Engineering, preferably in FSI.

• Strong hands-on experience designing enterprise Data Lakehouse platforms.

• Expertise in Databricks, Snowflake, Cloudera, Azure, AWS, or GCP.

• Strong knowledge of Iceberg, Hudi, Delta Lake, Object Storage, and Data Federation.

• Experience with Trino, Denodo, Dremio, Hive, Impala, and distributed compute platforms.

• Strong understanding of RAG, Vector DB, Graph DB, embeddings, and agentic workloads.

• Experience with Kafka, Flink, Spark Streaming, APIs, real-time data, and event-driven architectures.

• Strong knowledge of Terraform, Kubernetes/OpenShift, CI/CD, Git, Jenkins, and DevOps tools.

• Excellent understanding of data modeling, governance, metadata, data quality, and data products.