Capco is looking for a Consultant, Data Engineer to join our Technology & Engineering practice in Toronto. This is an exciting opportunity for an analytical professional who enjoys solving complex data challenges, validating large datasets, and delivering high-quality insights for leading financial services clients.
Working alongside multidisciplinary teams, you will help ensure the integrity, accuracy, and consistency of critical business data, enabling successful technology delivery and informed decision-making.
The Data Engineer will have strong Python, Pandas, and NumPy expertise to support data validation, reconciliation, and processing of large datasets. This role focuses on comparing multiple datasets, identifying data quality issues, automating data validation workflows, and supporting analytics initiatives. This is a hands-on engineering role with a strong emphasis on Python-based data processing and data quality management.
What We're Looking ForProgramming & Data Processing- Python (3+ years of hands-on experience)
- Pandas (Advanced)
- NumPy (Advanced)
- SQL
Data Engineering & Analytics- Experience processing and validating large datasets (millions of records)
- Data reconciliation and dataset comparison
- Data cleansing and transformation
- Data quality analysis and validation
- ETL/Data Pipeline fundamentals
- Root cause analysis of data discrepancies
Key Responsibilities- Validate and reconcile two or more datasets simultaneously.
- Build Python-based data validation and comparison frameworks.
- Use Pandas and NumPy extensively to analyze, transform, and validate large datasets.
- Develop automated processes to identify missing, duplicate, or inconsistent data.
- Investigate data quality issues and determine root causes.
- Create reports highlighting discrepancies and data quality metrics.
- Collaborate with business, analytics, and engineering teams to resolve data issues.
- Optimize large-scale data processing workflows.
Experience Required- 3-5+ years of experience in Data Engineering, Data Analytics, or Data Quality Engineering.
- Strong hands-on experience with:
- Experience working with large structured datasets.
- Experience comparing and reconciling data from multiple sources.
Day-to-Day Activities- Receive data extracts from multiple systems.
- Load and process large datasets using Python, Pandas, and NumPy.
- Compare datasets to identify gaps, inconsistencies, and anomalies.
- Build validation rules and automated quality checks.
- Investigate data issues and communicate findings to stakeholders.
- Create reusable scripts and frameworks for ongoing validation activities.
- Support data migration, onboarding, and integration projects.
Nice to Have- PySpark
- Azure Data Factory
- Databricks
- Power BI
- Git
- CI/CD
- Cloud platforms (Azure, AWS, GCP)
Ideal CandidateA hands-on Data Engineer with strong
Python, Pandas, and NumPy expertise who can efficiently validate, reconcile, and analyze multiple large datasets while building automated solutions to improve data quality and consistency.
Pay TransparencyThe salary range for this position is listed below. Additionally, this position may also be eligible to receive an annual discretionary/variable bonus payment.
Capco is committed to providing fair and equitable compensation to our people. Our compensation policies and salary ranges are designed to allow our people to progress through the salary range as they demonstrate strong performance and develop in their role over time. The base pay offered to selected candidates will be within the salary range and the placement will vary based upon a variety of factors, including, but not limited to job-related knowledge, skills, experience and internal equity.
Canada Pay Transparency
$92,000-$118,000 CAD
