Portugal
ambi.
Polaris Bank Limited
Head, Data & Intelligence Engineering
Portugal
Lagos, Portugal
PythonSQLAWS
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
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