MUTHOOT PAPPACHAN TECHNOLOGIES LIMITED
Website:
mptglobal.com
Job details:
Job Title: Senior Manager – AI, Analytics & Data Engineering
Location: Bangalore or Trivandrum
Experience:12–18 years
Education
- MBA / PGDM from a reputed institute
- B.Tech / BE in Computer Science, Information Technology, Engineering, Statistics or related discipline
- AWS Certifications preferred (Solutions Architect, Data Analytics, Machine Learning, AI Practitioner)
About the Role
We are looking for an experienced analytics leader to drive enterprise analytics, AI initiatives, reporting platforms, and data engineering for a leading NBFC. The role combines business strategy, data engineering, machine learning, generative AI, cloud architecture, and stakeholder management to enable data-driven decision making across lending, collections, customer acquisition, risk, finance, and operations.
The ideal candidate should possess strong business acumen along with deep technical expertise in AWS analytics services, AI-assisted development, and modern reporting platforms. The Business understanding till Report delivery
Key Responsibilities
Analytics & Business Intelligence
- Lead enterprise-wide analytics initiatives supporting business growth.
- Build executive dashboards and management reporting.
- Develop analytical frameworks for lending, customer lifecycle, portfolio performance, collections, and profitability.
- Generate actionable business insights through descriptive, diagnostic, predictive, and prescriptive analytics.
- Present findings to senior leadership and business stakeholders.
Data Engineering & AWS
Design and manage enterprise data platforms using AWS technologies including:
- Amazon Redshift
- AWS Glue
- AWS Lambda
- AWS Step Functions
Technical Responsibilities include:
- ETL/ELT pipeline development
- Data warehouse architecture
- Data modelling
- Performance optimisation
- Data quality monitoring
- Metadata management
- Cost optimisation
Artificial Intelligence & Machine Learning
Lead AI initiatives using:
- Amazon SageMaker
- Amazon Bedrock
- Foundation Models
- Retrieval Augmented Generation (RAG)
- Vector Databases
- Prompt Engineering
- Generative AI applications
Develop solutions such as:
- Customer intelligence
- Recommendation engines
- Churn prediction
- Lead scoring
- Document intelligence
- Intelligent assistants
- AI-powered reporting
- Predictive risk models
AI-Assisted Software Development
Champion AI-powered engineering practices using tools such as:
- GitHub Copilot
- Amazon Q Developer, Kiro
- Cursor
- ChatGPT
Responsibilities include:
- AI-assisted coding
- SQL generation
- Code review
- Documentation generation
- Test automation
- Workflow optimisation
Reporting & Visualisation
Develop enterprise reporting using:
- Amazon QuickSight
- Microsoft Power BI
- SQL
- Executive MIS
- KPI dashboards
Ensure:
- Automated reporting
- Self-service analytics
- Near real-time dashboards
- Data governance
Business Analysis
- Gather and document business requirements.
- Translate business problems into analytical solutions.
- Conduct process improvement studies.
- Build business cases for AI and automation projects.
- Work closely with Product, Operations, Risk, Finance, Sales, and Technology teams.
Team Leadership
- Lead and mentor analytics, BI, and data engineering teams.
- Define technical standards and best practices.
- Conduct architecture and code reviews.
- Drive innovation through AI adoption.
- Build analytics capability across the organisation.
Required Technical Skills
Cloud & Data
- AWS
- Redshift
- Glue
- S3
- Lambda
- EC2
AI & ML
- SageMaker
- Amazon Bedrock
- LLMs
- Prompt Engineering
- Machine Learning
- Python
- Scikit-learn
- Pandas
Programming
Reporting
- Amazon QuickSight
- Power BI
- Excel (Advanced)
Databases
Business Knowledge
Experience in one or more of the following:
- Gold Loans
- Personal Loans
- MSME Lending
- Loan Origination
- Collections
- Risk Analytics
- Customer Analytics
- Branch Performance
- Cross Sell Analytics
- Portfolio Management
- Regulatory Reporting
NBFC or Banking domain experience is preferred.
Leadership Competencies
- Strategic thinking
- Stakeholder management
- People leadership
- Problem solving
- Innovation mindset
- Excellent communication skills
- Project management
- Agile methodologies
- Decision-making under ambiguity
Preferred Experience
- 12–18 years in analytics, BI, or data engineering.
- Experience managing enterprise AWS analytics platforms.
- Proven track record delivering AI and ML solutions in production.
- Experience working with CXOs and business leadership.
- Experience implementing GenAI solutions within financial services.
Success Measures
- Improved business decision-making through analytics.
- Reduced reporting turnaround time.
- Increased automation of reporting and data pipelines.
- Successful deployment of AI/ML solutions into production.
- High adoption of self-service analytics.
- Optimised cloud cost and platform performance.
- Strong stakeholder satisfaction and business impact.
Nice-to-Have Skills
- MLOps
- Data Governance
- Data Catalog
- Apache Airflow
- Docker
- Kubernetes
- CI/CD
- Financial modelling
- Statistical analysis
- NLP
- Computer Vision
- Agentic AI frameworks
- Knowledge Graphs
- Model monitoring
- AI security and responsible AI
Click on Apply to know more.
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