Head, Data & Intelligence Engineering
Job Location:
Monthly Salary:
Experience Required:
Posted:
Application Deadline:
Vacancies:
Job Summary
About the Role
The Head Data & Intelligence Engineering owns the data platforms analytics and AI capabilities that power decision-making and personalized customer experiences at Polaris Bank. This is a leadership role directing four specialist disciplines Data Engineering Analytics & BI Data Science & AI and Data Governance through dedicated leads and engineers not as a hands-on individual contributor across all four.
Key Responsibilities
Data Engineering Oversight
- Direct the design of scalable reliable data pipelines warehouses and ETL infrastructure
- Set standards for data modeling and infrastructure architecture used across the banks data platforms
Analytics & BI Oversight
- Ensure the analytics function delivers dashboards reports and self-service tools that drive data-driven decisions across the bank
- Set standards for data visualization and reporting consistency
Data Science & AI Oversight
- Direct the development of AI/ML models supporting personalization fraud detection credit scoring and operational optimization
- Ensure model performance fairness and reliability are validated before production deployment
Data Governance Oversight
- Ensure data quality privacy and metadata management practices are enforced across all data assets
- Own the banks data governance framework and ensure regulatory compliance in data handling
Core Competencies
- Data platform strategy and technical leadership across engineering analytics and data science
- Working fluency in ML/AI model lifecycle management and MLOps practices
- Strong grounding in data privacy and regulatory compliance (NDPR and applicable banking data regulations)
- Stakeholder management across technology risk and business functions
Familiarity With Tools (used by the functions teams)
Python SQL Apache Spark Airflow Kafka Databricks Snowflake AWS Glue dbt; Power BI Tableau Looker Metabase; TensorFlow PyTorch Scikit-learn MLflow SageMaker Kubeflow; Collibra Informatica
Qualifications
- Bachelors degree in Computer Science Data Science Statistics or related field; advanced degree an advantage
- Demonstrated track record leading data engineering analytics or data science functions ideally in banking or financial services
Required Skills:
. Bachelors degree in Business Marketing Finance or related field; MBA or relevant postgraduate qualification is a plus. Minimum of 5-7 years experience in banking marketing or financial inclusion. Proven track record in developing and scaling customer-focused initiatives preferably targeting women. Strong understanding of gender finance customer segmentation and inclusive banking practices.
