Work Location: Mumbai (Lower Parel)
Role Summary
The BI Lead – Data Analytics will lead the organization's business intelligence and advanced analytics initiatives using the Databricks platform. The role will convert curated datasets from the enterprise data platform into dashboards, analytical models, and actionable insights supporting wealth management operations, portfolio analytics, and management reporting.
This role requires a hands-on analytics leader who can actively build data models, queries, and dashboards while guiding the analytics team and collaborating with business stakeholders.
Key Responsibilities
- Analytics Architecture
- Design and implement analytics frameworks using Databricks.
- Build analytics-ready data models for reporting and business intelligence.
- Optimize analytics workloads using Spark and SQL.
- Business Intelligence Development
Develop Dashboards And Analytics Solutions For
- Sales & Distribution: Client acquisition analytics, AUM growth tracking, Relationship manager performance
- Portfolio & Investment Analytics: Portfolio performance, Asset allocation insights, Product performance analytics
- Operations: Trade monitoring, Settlement analytics, Client service metrics
- Executive Reporting: Business performance dashboards, Revenue and profitability analytics
- Advanced Analytics
Leverage Databricks capabilities for advanced use cases: client segmentation, product analytics, investment insights, predictive analytics
- ML Lifecycle Management:
- Manage the end-to-end lifecycle of analytical and ML models, including model experimentation, version control, model validation, deployment, monitoring.
- Use Databricks ML capabilities (MLflow or similar frameworks) for model tracking and reproducibility.
- Model Deployment & Integration
- Deploy models for: batch scoring, near-real-time inference where required.
- Integrate model outputs into: BI dashboards, business applications, client analytics workflows.
- Model Monitoring & Performance Tracking
- Monitor model accuracy, drift, and performance.
- Track model metrics through Grafana or monitoring dashboards.
- Ensure models remain reliable and explainable.
- Self-Service Analytics: Enable business users to perform self-service analytics through BI tools, Define standards for dashboard design, KPI definitions, and analytics governance
- Collaboration: Work closely with the business stakeholders, understand business requirements and provide effective solutions, work in partnership with Data Engineering team to define curated datasets, ensure analytics requirements are incorporated into data platform design.
- Monitoring & Performance: Monitor analytics workloads and dashboard performance, use Grafana and CloudWatch metrics where applicable.
- Hands-on Technical Leadership: Actively develop SQL queries, analytical models, and dashboards, provide technical mentorship and review analytics artifacts, guide the analytics team in adopting best practices in data modeling and BI development.
- Agile Delivery: Work in an agile and iterative delivery environment, deliver analytics products and dashboards rapidly based on evolving business needs.
Key Technology Stack
- Analytics Platform: AWS Services, Databricks, Spark ML, MLflow
- Query & Processing: SQL, Apache Spark
- Visualization: Power BI / Databricks/ Tableau / similar BI tools
- Monitoring: Grafana, AWS CloudWatch
- DevOps: GitLab
Experience
- 8–12 years in BI / analytics roles
- Strong hands-on experience building dashboards and analytical models
- Experience working with Databricks or Spark-based analytics environments
- Experience in wealth management / capital markets preferred
