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Senior ETL Engineer

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SeniorHybryda·GdańskFull-time

#463121·Dodano 15 dni temu·0

Źródło: justjoin.it

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Tech Stack / Keywords

Data analysisSQLRisk ManagementBusiness Intelligence (BI)ETLProvisioningBusiness AnalysisPerformance optimizationTestingAgile

Podsumowanie oferty

The role focuses on building and maintaining data pipelines and warehousing solutions for banking, including Balance Sheet Stress Testing and Regulatory Reporting. You will work with Snowflake, SQL, and ETL/ELT technologies to implement banking requirements and financial data models.

Wymagania

Key Requirements:

Strong hands-on experience with Snowflake, SQL, and large-scale data warehousing solutions.
Extensive experience developing ETL/ELT processes in complex environments.
Deep understanding of banking data, including Balance Sheet Management and Regulatory Reporting.
Proven skills in data analysis, validation, and reconciliation across systems.
Strong business analysis capabilities, including stakeholder management and translating business needs into technical solutions.
Experience with statistical data preparation for models.
Understanding of data governance and regulatory requirements affecting banking data.
Excellent communication skills to interface with technical and business stakeholders.

Nice to have:

Experience with regulatory frameworks such as EBA, Basel, or ICAAP.
Knowledge of Data Vault and cloud data platforms.
Experience in Agile/SAFe environments.
Familiarity with data visualization tools like Power BI and Tableau.

Obowiązki

Main Responsibilities:

Design, develop, and maintain enterprise-grade ETL/ELT pipelines using Snowflake and modern data technologies.
Analyze and interpret banking requirements related to Balance Sheet Stress Testing and risk management processes.
Collaborate with analysts in finance, treasury, and risk to ensure accurate implementation of business logic.
Build and optimize data warehousing solutions for aggregation, transformation, and reporting of financial data.
Develop data models for stress testing simulations and management reporting.
Ensure data quality, governance, and regulatory compliance standards are met.
Drive performance automation and continuous improvements in data processing frameworks.

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