Risk Manager_SUPPORT SERVICES_0898_1288_1082593
Candidate Experience site · Mumbai, Maharashtra, India
Strong hiring record · median 29 days open
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In its favour
- Posted today
- Still listed on the employer's own board
Role
Risk BI
Experience
4–12 Years
Domain
Retail/Commercial Banking (Lending, Cards, Deposits, Risk, Collections, Regulatory)
Desired strong expertise in SQL, Power BI, Python, Airflow, and CI/CD pipelines, combined with hands on Data Engineering capabilities. The role involves designing and delivering enterprise grade BI solutions, automating data pipelines, and enabling data driven decision making across key banking portfolios. Should be well versed with Risk background & Risk KPIs.
Overview
To Lead and manage business intelligence initiatives with a strong emphasis on automation, data democratization, standardization, and governance. The role requires expertise in Data modelling, data management, and dashboard-driven insights. . It ensures timely and high-quality inputs from a data design and architecture perspective, facilitating the storage of customer data from various sources, with a primary focus on aiding risk management.
Key Responsibilities
Automate MIS and Reporting
Ensure all Management Information Systems (MIS), reports, and risk dashboards are automated and accessible to stakeholders through Power BI or other visualization tools.
Develop Action-Oriented Dashboards
Create multiple dashboards with actionable insights for risk monitoring using various AI tools.
Organize Data Efficiently
Structure data at the customer and product levels to facilitate easy analysis and transaction-level insights and aid hindsighting.
Bureau Reporting
Manage and automate bureau reporting processes.
Prepare Review Decks
Compile various decks for timely reviews by various stakeholders, including CRO’s office, board committees and top management.
Automate Regulatory Reports
Streamline the automation of various regulatory reports.
Deliver Adhoc Regulatory Requirements
Ensure timely delivery of adhoc regulatory requirements from the risk team.
Risk Data Mart Creation and Management
Design, develop and maintain a central repository of all risk features that gets repeatedly used by various users within the risk team. Risk data mart will ensure re-usability of data elements without duplication of efforts by each users generating huge efficiencies.
Collaborate Across Teams
Work closely with risk. compliance, product teams, IT, data engineers, and other governance teams to ensure consistent data management.
Generate Collection Data Insights
Create insights from collection data for use by the risk team for various products
Business Intelligence & Reporting
- Build and maintain enterprise dashboards and reports using Power BI (DAX, data modelling, Power Query).
- Translate business requirements into analytical datasets, KPIs, and visualizations for business, risk, and finance groups.
Manage BI lifecycle
design → development → testing → deployment → support.
- Data Engineering & Pipelines
- Design and orchestrate scalable ETL/ELT pipelines using Apache Airflow.
- Integrate data from DWH & other core banking systems, credit bureaus, and transaction systems.
- Ensure data quality, lineage tracking, schema evolution, and data governance compliance.
- SQL & Data Modeling
- Write complex SQL queries, improve query performance, create stored procedures, and manage large-scale banking datasets.
- Build fact/dimension models for analytics consumption layers.
- Implement incremental refresh and optimize semantic models for Power BI.
- CI/CD & DevOps for Data
- Implement CI/CD pipelines for BI and data workflows (Git, Azure DevOps, GitHub Actions, etc.).
- Automate deployment of Power BI assets, SQL scripts, Airflow DAGs, and Python code across dev/uat/prod.
- Establish version control, code review processes, unit testing, and release governance.
- Banking Domain Expertise
Build KPIs, dashboards, and insights around
o Portfolio performance
o NPA/ECL metrics
o Roll rates & vintage curves
o Acquisition funnels
o Regulatory/management reporting
- Ensure metric standardization, data dictionary management, and governance alignment.
- Leadership & Collaboration
- Lead BI developers/data analysts in delivering high-quality outputs.
- Conduct code reviews, enforce best practices, and ensure on-time delivery.
- Drive data & BI modernization initiatives across the bank.
________________________________________
Required Technical Skills
SQL (Advanced)
Indexing, Query optimization, Stored Procedures.
Power BI (Expert)
Data modelling, DAX, RLS, incremental refresh, composite models, deployment pipelines.
Python
pandas, numpy, SQL connectors, automation scripts, scheduling.
Airflow
DAG design, custom operators, task orchestration, SLAs, retry logic.
CI/CD
Automated deployments, code quality frameworks.
Data Engineering
ETL/ELT design, data modeling, data validation frameworks, structured & semi-structured data handling.
- Experience with relational databases (SQL Server, Oracle, Postgres, MySQL).
________________________________________
Preferred Skills
- Exposure to cloud data platforms (Azure Data Factory/Synapse, AWS Redshift/Glue, GCP BigQuery).
- Knowledge of Tableau / Power BI Admin features.
- Understanding of risk analytics metrics and regulatory reporting.
________________________________________
Qualifications
- Bachelor’s or Master’s degree in Engineering, Computer Science, Information Systems, Statistics, or equivalent.
- Banking BI/Data experience is mandatory.
________________________________________
Success Indicators
- Highly reliable and automated BI + data pipelines
- Strong data quality and governance adherence
- High adoption of dashboards across Risk teams
- Consistent on-time delivery of insights and pipelines
________________________________________
Skills
- SQL
- Power BI
- Python
- Airflow
- DAX
- ETL
- ELT
- Git
- Azure DevOps
- GitHub Actions
- Pandas
- NumPy
- SQL Server
- Oracle Database
- PostgreSQL
- MySQL
- Azure Data Factory
- Synapse
- AWS
- Redshift
- AWS Glue
- GCP
- BigQuery
- Tableau
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