Job Title: Data Analyst

Job Location: 100% Remote in Canada

Job Duration: 3+ Months Contract

Pay Rate: CA$40/hr to CA$50/hr

Job Description:

• Designing Scalable Data Architecture: Develop and implement cloud-based data architectures on GCP to support banking analytics and reporting needs.
• Data Modeling & Structuring: Build data models optimized for performance, scalability, and compliance with banking regulations
• Cloud Data Platform Design: Architect solutions using GCP services such as BigQuery to ingest, process, and store large-scale data for financial analytics.
• ETL/ELT Pipelines: Design, develop, and manage robust ETL/ELT pipelines to extract data from various banking sources, transform it into required formats, and load it into data lakes (GCP).
• Data Integration: Integrate data from disparate banking systems (SAP Banking Systems, CRM, Salesforce) and external sources into GCP.
• Data Quality Assurance: Implement data validation checks, monitoring, and alerts to ensure the accuracy, consistency, and reliability of financial data.
• Data Visualization: Design and develop Tableau dashboards to provide actionable insights into banking metrics, including loan performance, credit risk, profitability, and customer segmentation.
• Interactive Reports for Stakeholders: Build interactive, easy-to-understand reports for both technical and non-technical banking stakeholders (finance, risk management, operations, senior executives, etc.).
• Liaise with Business Stakeholders: Regularly engage with business stakeholders (finance, risk management, operations etc.) to ensure the data solutions meet the specific needs of the banking business.
• Production Support: Provide ongoing support for deployed data pipelines and Tableau dashboards, troubleshooting issues related to data quality, performance, and integration.
• Incident Management: Handle production incidents promptly, resolving data issues and ensuring the availability of key banking metrics for reporting and decision-making.
• Stay Current with Industry Trends: Keep up to date with the latest developments in data engineering, cloud technologies (especially GCP), and data visualization trends, ensuring that the team is leveraging best practices.
• Innovation: Continuously identify opportunities to innovate the data architecture and data analytics workflows, exploring new tools, technologies, and methodologies that can improve the efficiency and scalability of the banking data infrastructure.
• Technical Documentation: Create comprehensive documentation for data pipelines, architecture designs, and Tableau reports, ensuring knowledge sharing within the team and easy onboarding for new team members.
• Best Practices: Document and promote best practices in data engineering, security, cloud optimization, and dashboard development to ensure a high standard of work.

Top Skills:

• Five or more years of experience in data engineering or software development, preferably in the banking, finance, or other regulated industries.
• Proven experience working with large-scale data systems and cloud platform.
• Experience in financial services is highly desirable (working with transactional data, credit risk, regulatory compliance, etc.).
• Experience in business performance reports, process improvement and risk assessment is highly desirable.
• Advanced knowledge of ETL (Extract, Transform, Load) and ELT processes, including data ingestion, transformation, and cleaning for large-scale datasets.
• Experience in managing data pipelines, ensuring data quality and reliability across multiple systems.
• Tableau: Proficiency in developing interactive dashboards and reports to visualize key business and financial metrics.
• Strong understanding of data governance best practices, ensuring data quality, consistency, and compliance with industry standards.
• Experience in implementing data validation checks, automated testing, and monitoring frameworks to ensure the integrity of data across pipelines.
• Ability to transform business requirements into technical solutions, collaborating with cross-functional teams (finance, risk management, operations, etc.). Experience with financial analytics: Knowledge of banking-specific metrics such as credit risk, impaired loans, and operational KPIs.

Project Description: Complex Lending

Team size: Small (1-5)

Number of Years Experience: 5

Level of Communication: 4