Cloud Data Engineer - Banking Domain

Job summary

Design and maintain enterprise data warehouse solutions, financial data models, and scalable ETL/ELT pipelines for finance and lending domains. Collaborate with business stakeholders to define data requirements, ensure data quality and governance, troubleshoot issues, and support cloud platform modernization.

Job details

Role : Cloud Data Engineer - Banking Domain Location : Ottawa / Toronto (Hybrid) Must have : Finance domain Role Summary We are seeking a Cloud Data Engineer with strong Data Warehouse and Data Modeling experience, coupled with deep understanding of Finance products and loan data domains. The ideal candidate will be able to bridge business and technology by translating complex financial product requirements into scalable data models and enterprise data warehouse solutions. Key Responsibilities • Design and develop enterprise-scale Data Warehouse solutions supporting finance and loan business domains. • Analyze and model complex financial products, loan portfolios, transactions, fees, and related finance data structures. • Develop and maintain scalable ETL/ELT pipelines using Python and SQL. • Create and optimize dimensional and normalized data models for analytics and reporting. • Collaborate with business stakeholders, product owners, and SMEs to define source-to-target mappings and data requirements. • Ensure data quality, reconciliation, and governance across finance data platforms. • Perform data analysis, troubleshooting, and root cause investigation for data issues. • Contribute to cloud-based data platform modernization initiatives. Required Skills • Strong experience in Data Warehousing (DWH), Dimensional Modeling, OLTP/OLAP concepts, Facts & Dimensions. • Expertise in SQL development and query optimization. • Strong Python programming skills for data engineering and automation. • Experience designing enterprise data models and data integration solutions. • Deep understanding of Finance products, preferably: o Commercial Lending o Corporate Banking o Loan Servicing o LoanIQ or similar loan management platforms o Finance accounting/subledger concepts • Experience working with large-scale financial data platforms. • Strong analytical, troubleshooting, and problem-solving skills. Nice to Have • Databricks and PySpark experience. • Delta Lake. • Snowflake, Synapse, Redshift, or BigQuery. • Airflow/Astronomer. • Azure cloud services. • Experience with metadata-driven ETL frameworks and data governance. Preferred Experience • 8+ years in Data Engineering/Data Warehousing. • 3+ years working with Finance, Banking, or Lending domains. • Experience supporting enterprise reporting, regulatory, accounting, or finance data initiatives.

What you’ll do

Design and maintain enterprise data warehouse solutions, financial data models, and scalable ETL/ELT pipelines for finance and lending domains. Collaborate with business stakeholders to define data requirements, ensure data quality and governance, troubleshoot issues, and support cloud platform modernization.

Requirements

Requires strong data warehousing, dimensional modeling, SQL, and Python experience, along with deep knowledge of finance products and loan data. The preferred experience is 8+ years in data engineering or warehousing and 3+ years in finance, banking, or lending; cloud and big-data tools are advantageous.

Listed skills

• Microsoft Azure · Preferred
• SQL · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Data Warehousing
• Dimensional Modeling
• SQL
• Python
• ETL/ELT
• Enterprise Data Modeling
• Data Integration
• Finance Domain
• Commercial Lending
• Corporate Banking
• Loan Servicing
• Data Quality
• Data Governance
• Databricks
• PySpark
• Azure

Job areas

• Data & Analytics
• Technology
• Finance & Accounting
• Software

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