Data Warehouse Architect with Banking/Financial Domain

Location: Iselin, NJ and New York City, NY

We are seeking an experienced Data Warehouse Architect with strong expertise in the Banking/Financial Services domain to design, develop, and optimize enterprise-scale data warehouse and analytics solutions. The ideal candidate should have hands-on experience with Python, PySpark, SQL, Databricks, Snowflake, and ETL/ELT frameworks while working on large-scale financial data platforms, regulatory reporting, risk analytics, and transactional systems.

Mandatory Skills

• Python
• PySpark
• SQL
• Databricks
• Snowflake
• ETL/ELT Development
• Data Warehousing Architecture
• Banking / Financial Services domain experience

Key Responsibilities

• Design and architect scalable enterprise data warehouse solutions for banking and financial systems.
• Develop and optimize ETL/ELT pipelines using Python, PySpark, SQL, and Databricks.
• Build and maintain data models, data marts, and Snowflake-based cloud data warehouse solutions.
• Integrate data from multiple banking systems including payments, loans, trading, risk, compliance, and customer platforms.
• Implement data governance, data quality, metadata management, and security best practices.
• Optimize performance of large-scale data processing and transformation workloads.
• Work closely with business stakeholders, data engineers, analysts, and enterprise architects to define data strategies.
• Support regulatory reporting, financial analytics, fraud detection, and risk management initiatives.
• Design real-time and batch data ingestion frameworks using modern ELT/ETL methodologies.
• Ensure scalability, reliability, and high availability of enterprise data platforms.
• Lead migration and modernization efforts from legacy data warehouses to cloud-based platforms.
• Mentor development teams and establish best practices for data engineering and architecture.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
• 10+ years of experience in Data Warehouse/Data Engineering/Data Architecture roles.
• Strong hands-on expertise in Python, PySpark, SQL, Databricks, Snowflake, and ETL/ELT tools.
• Experience designing cloud-based data platforms and modern data lake architectures.
• Strong understanding of data modeling concepts including Star Schema and Snowflake Schema.
• Experience handling large volumes of structured and semi-structured financial data.
• Strong understanding of banking and financial services business processes.
• Experience with performance tuning, data optimization, and query optimization.
• Excellent communication and stakeholder management skills.