Head, Data & Intelligence Engineering

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. What You'll Do

• Data Engineering Oversight: Direct the design of scalable 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. What We're Looking For
• Core competencies include data platform strategy and technical leadership across engineering, analytics, and data science; familiarity with ML/AI model lifecycle management and MLOps; strong grounding in data privacy and regulatory compliance (NDPR and banking data regulations); stakeholder management across technology, risk, and business functions.
• Demonstrated track record leading data engineering, analytics, or data science functions, ideally in banking or financial services.
• Required education: Bachelor's degree in Computer Science, Data Science, Statistics, or related field; advanced degree a plus.
• Tools and technologies familiarity across Python, SQL, Spark, Airflow, Kafka, Databricks, Snowflake, AWS Glue, dbt; Power BI, Tableau, Looker, Metabase; TensorFlow, PyTorch, Scikit-learn, MLflow, SageMaker, Kubeflow; Collibra, Informatica.
• NDPR familiarity and data privacy/regulatory compliance awareness; ability to manage stakeholder expectations and deliver data-driven outcomes. Nice to Have
• Advanced degree in a related field; Banking/financial services experience preferred. Compensation & Benefits
• Salary and benefits not disclosed at this time.