Senior Data Engineer (Banking, Snowflake, BigData)

165 PLN/ godz./ godz.B2BB2B (netto)

SeniorHybryda·WarszawaFull-time·B2B

#465662·Dodano 3 dni temu·0

Źródło: justjoin.it

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Tech Stack / Keywords

Snowflake SQL ETLELTBanking DatabankingEBAAgileSAFeTableau

Podsumowanie oferty

Join a global banking client’s team working in Risk and Regulatory Reporting. You will deliver data engineering in Snowflake end to end, from requirements analysis and data investigations to production implementation.

Wymagania

Strong hands-on experience with Snowflake, SQL and large-scale data warehousing.
Extensive experience building and maintaining ETL/ELT processes in complex enterprise environments.
Deep understanding of banking data, e.g. Balance Sheet Management, Stress Testing, Treasury and Liquidity, Finance and Regulatory Reporting, Risk Management, Capital Adequacy.
Proven ability to analyse, validate, reconcile and aggregate data across multiple source systems.
Strong business analysis skills: requirements gathering, process modelling, stakeholder management and translating business needs into technical solutions.
Experience with statistical analysis and data preparation for analytical models.
Understanding of data governance, data quality frameworks and regulatory requirements for banking data.
Excellent communication skills with both technical and business stakeholders.
Fluent English.

Nice to have:

Experience with EBA, ECB, Basel, ICAAP, ILAAP, IRRBB or other regulatory stress testing frameworks.
Knowledge of Data Vault, dimensional modelling and cloud data platforms.
Experience in Agile/SAFe environments.
Power BI, Tableau or similar reporting tools.

Obowiązki

Design, develop and maintain enterprise-grade ETL/ELT pipelines in Snowflake.
Analyse banking business requirements around Balance Sheet Stress Testing, scenario analysis, capital adequacy, liquidity and risk management.
Work closely with business analysts and finance, treasury, risk and regulatory stakeholders to implement business logic accurately.
Build and optimise data warehousing solutions for large-scale aggregation, transformation and reporting of financial data.
Develop data models that support stress testing simulations, statistical analysis and management reporting.
Ensure data quality, reconciliation, lineage, governance and regulatory compliance.
Prepare and provision data for downstream analytical, reporting and regulatory layers.
Drive performance optimisation, automation and continuous improvement of data platforms.

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