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 bank's 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 bank's 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 function's 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
Requirements
Qualifications
- Bachelor's 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
Skills Required
- Bachelor's degree in Computer Science, Data Science, Statistics, or related field
- Advanced degree (Master's or PhD) in relevant field
- Demonstrated track record leading data engineering, analytics, or data science functions
- Experience in banking or financial services (preferred)
- Leadership of cross-disciplinary teams (Data Engineering, Analytics & BI, Data Science & AI, Data Governance)
- 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: 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
Polaris Bank Limited Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Polaris Bank Limited and has not been reviewed or approved by Polaris Bank Limited.
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Flexible Benefits — Feedback suggests that certain packages, including split-salary structures and access to financial loans, are viewed as helpful for budgeting and financial flexibility. Some employees also reference health insurance schemes that contribute to perceived benefits breadth.
Polaris Bank Limited Insights
What We Do
Polaris Bank is a forward-thinking financial institution committed to delivering customer-first banking experiences across Nigeria, offering tailored solutions for individuals, SMEs, corporates, and government institutions.
