- Partner with Portfolio Management, Asset Allocation, Trading, Performance, Risk, Research, and other investment teams
- Develop and maintain analytical data products supporting investment workflows
- Translate financial and analytical requirements into scalable data solutions
- Manage performance, attribution, time-series, holdings, positions, exposures, and aggregated analytics datasets
- Ensure investment datasets are accurate, validated, timely, and well-governed
- Own analytical product lifecycles from data ingestion and transformation through delivery and continuous evolution
- Define requirements, priorities, operating expectations, and success measures with stakeholders
- Design scalable data models and transformation pipelines
- Develop Power BI and Streamlit analytical experiences
- Build and maintain ETL/ELT pipelines for investment processes and recurring analytical workflows
- Implement data quality controls, reconciliation, monitoring, and operational runbooks
- Contribute reusable dbt models, standards, templates, documentation, lineage, and semantic-layer components
- Support cloud-native platform modernization and AI-enabled analytical workflows
- Diagnose issues across data dependencies, transformation logic, orchestration, and reporting layers

Requirements

Strong Python development skills

Strong understanding of data engineering, analytics engineering, data modeling, and best practices

Experience building scalable ETL/ELT pipelines and analytical data models using dbt or comparable frameworks

Experience with transformation logic, testing, documentation, lineage, and reusable modeling practices

Experience with Google Cloud Platform and BigQuery

Experience with Prefect, Dagster, or Airflow

Familiarity with GitHub, code reviews, CI/CD concepts, Docker, and contemporary software development practices

Experience building Power BI solutions, semantic models,



and analytical applications

Understanding of data quality, validation, reconciliation, monitoring, and governance

Solid understanding of investment and financial analytics concepts

Ability to understand investment workflows and translate business and financial requirements into scalable solutions

Experience working with financial datasets or investment analytics is highly desirable

5+ years of relevant experience for intermediate candidates; 8+ years for senior candidates

Experience at the intersection of finance, analytics, data engineering, and technology

Experience building data products, analytical solutions, modern reporting capabilities, or production-grade data pipelines

Demonstrated ability to deliver and support production-grade data and analytics solutions

Advanced proficiency in French; daily communication with English- and French-speaking clients and partners across Canada via email and phone calls

Undergraduate or master’s degree in a relevant field preferred, not required

Core Competencies

Demonstrates expertise in developing and maintaining analytical data products, building scalable ETL/ELT pipelines, and ensuring data quality and governance. Proficient in translating financial requirements into data solutions while collaborating with investment teams and stakeholders.

Highest-signal resume keywords

Python Development

ETL/ELT Pipeline Development

Data Engineering

Power BI Solutions

Google Cloud Platform

ATS Optimization Keywords

Hard Skills

Data Modeling

Analytical Data Products

Transformation Logic

Data Quality Controls

Investment Analytics

Dbt Framework

BigQuery

Prefect

Dagster

Airflow

Soft Skills

Collaboration

Communication

Problem-Solving

Industry Keywords

Investment Workflows

Financial Datasets

Analytics Engineering

Data Governance

Operational Runbooks

Tools & Technologies

Power BI

Streamlit

GitHub

Docker

CI/CD

📌 Senior Analyst, Quantitative Data Science (Winnipeg)
🏢 Jobtailor
📍 Winnipeg