Data Architect/Modeler

We are seeking an experienced Data Architect with strong Data Modeling expertise and hands-on Data Engineering capabilities to support enterprise data initiatives within the Financial Services industry. The ideal candidate will design scalable cloud-based data platforms, develop enterprise data models, and deliver modern data architecture solutions that support analytics, reporting, regulatory compliance, and business intelligence initiatives. Responsibilities Design and implement enterprise-wide data architecture solutions for large-scale financial services environments. Develop conceptual, logical, and physical data models supporting operational, analytical, and reporting platforms. Architect and support cloud-native data platforms including enterprise data lake, warehouse, and lakehouse ecosystems. Develop ETL/ELT pipelines, data ingestion frameworks, and transformation processes. Design scalable batch and real-time data integration solutions for structured and semi-structured data. Support Master Data Management (MDM) initiatives across security, account, client, and reference data domains. Collaborate with enterprise architecture, governance, security, compliance, and business teams to establish enterprise data standards. Implement metadata management, data lineage, governance, and data quality frameworks. Optimize enterprise data platforms for scalability, reliability, performance, and cost efficiency. Support regulatory, audit, risk, and compliance reporting requirements. Participate in cloud migration and modernization initiatives involving legacy and distributed data systems. Enable analytics, AI/ML, reporting, and business intelligence capabilities through trusted enterprise data solutions. Preferred Skills Experience supporting enterprise modernization and cloud transformation initiatives. Exposure to real-time analytics and distributed data platforms.

8 10 years of experience in Enterprise Data Architecture and Data Modeling across modern data platforms. Hands-on experience with Data Engineering and development of scalable enterprise data pipelines. Strong expertise in cloud-based data platforms such as Snowflake, Databricks, and distributed data processing technologies. Experience with on-premise data platforms and legacy data warehouses such as Oracle Exadata. Strong understanding of data warehouse, data lake, and lakehouse architectures. Experience designing and implementing ETL/ELT frameworks using Spark, Snowflake Tasks, Streams, or similar technologies. Expertise in Master Data Management (MDM), enterprise data governance, metadata management, data lineage, and data quality. Strong SQL skills with programming experience in Python, PySpark, or Snowpark. Experience with dbt (Data Build Tool) for data transformation, modeling, ELT development, testing, documentation, and version control. Experience with Azure, AWS, or GCP and integration with Snowflake and Databricks. Familiarity with API integrations, Kafka, Spark Streaming, and event-driven architectures. Understanding of enterprise security, compliance, RBAC, data masking, and encryption. Experience working in Agile environments and collaborating with cross-functional teams. Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field., Knowledge of enterprise architecture and data governance frameworks. Financial Services, Investment Management, or Wealth Management industry experience. Excellent communication, collaboration, and stakeholder management skills.