Analytics Engineer

Role Description

Phillips & Cohen Associates Ltd. is seeking an Analytics Engineer to support the Strategy & Analytics function and help identify opportunities that drive performance. The ideal candidate should demonstrate strategic curiosity, challenge assumptions, and translate analysis into insights.

This role combines analytics engineering, data modeling, automation, and applied analytics to transform data into actionable insights, connecting data analysis to execution to accelerate growth and competitive advantage. The Analytics Engineer plays a critical role in turning data into a strategic asset, ensuring the business can rely on accurate, timely insights to drive performance and growth.

• Support analytics use cases (segmentation, forecasting, A/B testing).
• Develop, implement, and optimize debt recovery processes, including dialer, scoring, and portfolio segmentation.
• Engineer new data assets and derived datasets when required information is not available in existing source systems.
• Develop scalable data models and schemas to support portfolio valuation, forecasting, reporting, and operational analytics.
• Eliminate conflicting metrics and definitions, creating a single source of truth across teams.
• Build and maintain automated end-to-end analytics workflows, including scheduling, orchestration, alerts, and reporting.
• Implement data quality rules, validation logic, automated QA checks, and monitoring frameworks to ensure data integrity.
• Perform exploratory data analysis to identify trends, data gaps, and metric behavior related to portfolio performance.
• Translate business questions and strategy needs into technical requirements, datasets, and analytical solutions.
• Create reports, dashboards, and analytical outputs that are usable and interpretable by non-technical stakeholders.
• Optimize SQL queries and ETL/ELT processes for performance, accuracy, and reliability.
• Collaborate closely with analytics, engineering, and business partners to align data definitions, metrics, and logic.
• Document data pipelines, models, transformations, business rules, and data dictionaries to support governance and continuity, ensuring consistent metric definition across the organization.

Qualifications

• Minimum of 3 years of experience in analytics engineering, data engineering, data analytics, or similar hybrid analytics roles.
• Advanced SQL skills with hands-on experience building scalable transformations and data models.
• Proficiency in programming languages such as SAS, Python, or R for analytics, automation, and modeling.
• Demonstrated experience designing datasets and data architecture to support advanced analytics and forecasting.
• Experience with BI and visualization tools such as Power BI, Tableau, or Looker.
• Strong analytical thinking with the ability to translate complex data into actionable business insights.
• Ability to work effectively in ambiguous, open-ended problem spaces.
• Understanding of statistical concepts and predictive modeling techniques.
• Strong written and verbal communication skills with both technical and non-technical audiences.
• Experience developing SQL Server jobs, stored procedures, triggers, or similar database objects.
• Familiarity with Git or version control systems.
• Background in non-performing debt industry, financial services, portfolio analytics, forecasting, or operations analytics is a plus.