Expert Snowflake Data Engineer

Quick Facts

• Role: Expert Snowflake Data Engineer

Description

Design, develop, and maintain advanced ETL/ELT pipelines in Snowflake to support large-scale financial data processing for banking use cases. Translate complex regulatory and financial requirements—especially stress testing, capital adequacy, liquidity, and risk—into scalable data solutions while ensuring data quality, reconciliation, and governance. Collaborate with business and Finance/Treasury/Risk/Regulatory stakeholders to deliver data for analytics, reporting, and regulatory layers.

Responsibilities

• Design, develop, and maintain advanced ETL/ELT processes using Snowflake and modern data engineering technologies

• Analyze banking requirements for balance sheet stress testing, scenario analysis, capital adequacy, liquidity, and risk management

• Convert complex regulatory and financial requirements into scalable data solutions

• Partner with business analysts and Finance, Treasury, Risk, and regulatory stakeholders to implement business logic

• Build and optimize data warehouse solutions for aggregation, transformation, and reporting of large volumes of financial data

• Develop data models for stress testing simulations, statistical analysis, and management reporting

• Ensure data quality, reconciliation, data lineage, data governance, and regulatory compliance

• Prepare and provide data for analytical, reporting, and regulatory layers

• Perform deep data analysis, validation, and reconciliation across multiple source systems

• Optimize performance, automate processes, and continuously improve data platforms and processing frameworks

Requirements

• Very strong practical knowledge of Snowflake, SQL, and data warehouses handling large data volumes

• Extensive experience creating and maintaining ETL/ELT processes in complex enterprise environments

• Deep knowledge of banking data domains: balance sheet management, stress testing, Treasury, liquidity, Finance, regulatory reporting, risk management, and capital adequacy frameworks

• Proven experience in complex data analysis, validation, reconciliation, and aggregation from multiple source systems

• Strong business analysis skills: requirements gathering, process modeling, stakeholder management, and translating business needs into technical solutions

• Practical experience with statistical analysis and preparing data for analytical models

• Knowledge of data governance, data quality standards, and regulatory requirements for banking data environments

• Ability to communicate effectively with technical and business stakeholders

• Excellent English proficiency (spoken and written)

Benefits

• Private medical care

• Subsidy for a sports card

• Ongoing support from a dedicated consultant

• Employee referral program