
Lead Data Architect
5 days ago
Our organization is seeking an accomplished data leader to craft and enhance data solutions for our financial clients.
This role is ideal for someone with profound expertise in ETL development, data modeling, and financial data domains, particularly within credit unions and banking systems.
The successful candidate will be instrumental in designing and maintaining scalable data pipelines using Snowflake, Matillion, and Python, while leveraging knowledge of core banking systems like Fiserv and medallion architecture to deliver high-impact solutions.
Key Responsibilities:- Design, build, and maintain robust ETL pipelines using Snowflake, Matillion, and Python.
- Develop and optimize data models to support analytics and reporting across the organization.
- Implement and maintain medallion architecture (Bronze, Silver, Gold layers) for scalable data processing.
- Write complex SQL queries for data manipulation and analysis.
- Collaborate with stakeholders to understand data requirements for strategic initiatives.
- Integrate data from core banking systems (e.g., Fiserv) and other financial platforms.
- Ensure data quality, governance, and security across all pipelines.
- Use Python for data transformation, automation, and orchestration tasks.
- Troubleshoot data issues and optimize data pipelines for performance.
- 10–15 years of experience in data engineering, with a strong focus on ETL development.
- Hands-on expertise with Snowflake, Matillion, and Python.
- Experience in designing and implementing data models using medallion architecture.
- Must have knowledge of banking and credit union data domains.
- Expertise in working with core banking systems like Fiserv.
- Experience implementing medallion architecture (Bronze, Silver, Gold) for data organization and management.
- Advanced skills in SQL for complex queries, performance tuning, and data manipulation.
- Understanding of data security and governance in financial institutions.
- Experience with data analytics and business intelligence tools like Power BI.
- Knowledge of regulatory requirements in banking and credit unions.
- Experience working in a financial institution or with financial data.
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