Swoon
Senior Data Engineer
Build and maintain ETL pipelines, analyze financial data with Python/SQL, and create dashboards in Power BI to support treasury and finance decisions.
- Compensation
- Not disclosed
- Location
- Toronto, Canada
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 8+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 8-10 years of strong experience in Python, SAS, and SQL
- Power BI, DAX, and M Code for dashboard development
- Proficiency in MS 365 Suite: Office, Power Automate, SharePoint, OneDrive
- Advanced SQL Server configuration for high-throughput analytics (memory allocation, parallel query execution)
- Experience with partitioned tables, indexed views, and columnstore indexes
- Deep understanding of SQL Server recovery models, backup/restore strategies, and disaster recovery planning
- Design and implementation of ETL pipelines with incremental loads and change data capture
- Data staging and processing large-scale datasets efficiently
- Experience with star/snowflake schemas, fact/dimension modeling, and slowly changing dimensions
- Batch processing pipelines using Python and SQL
- Knowledge of RDBMS, NoSQL, and data file formats (CSV, Parquet, JSON)
- Translate business requirements into scalable, optimized data models
- Strong experience with AWS (Redshift, Glue, MLOps)
Full description
Analytics Data Engineer – Treasury/FinanceDuration: 6 months
Extension Potential: No
FTE Conversion: No
Work Hours: 9:00 AM – 5:00 PM
Location: Remote or Hybrid (must be able to visit the office for technical issues or special occasions)
Key Responsibilities
- Data Collection & Preparation: Gather data from multiple sources, clean and preprocess to ensure accuracy and consistency.
- Statistical Analysis: Apply statistical modeling techniques (hypothesis testing, regression, clustering) to identify patterns, trends, and relationships.
- Programming & Analysis: Use Python, SQL, or R to analyze data and uncover insights that address business challenges such as customer behavior, operational efficiency, and cost optimization.
- Visualization & Reporting: Create dashboards and visualizations using Tableau, Power BI, or matplotlib to simplify complex data for stakeholders and support data-driven decisions.
- Data Engineering & ETL: Develop robust ETL pipelines to handle large datasets from IBM Netezza/Hadoop and other sources, ensuring efficient processing and transformation.
- Advanced Analytics: Incorporate predictive modeling and machine learning techniques to solve complex business problems.
- Collaboration: Work with business teams to translate requirements into scalable, actionable data solutions.
Must-Have SkillsProgramming & Tools
- 8-10 years of strong experience in Python, SAS, and SQL
- Power BI, DAX, and M Code for dashboard development
- Proficiency in MS 365 Suite: Office, Power Automate, SharePoint, OneDrive
- Advanced SQL Server configuration for high-throughput analytics (memory allocation, parallel query execution)
- Experience with partitioned tables, indexed views, and columnstore indexes
- Deep understanding of SQL Server recovery models, backup/restore strategies, and disaster recovery planning
- Design and implementation of ETL pipelines with incremental loads and change data capture
- Data staging and processing large-scale datasets efficiently
- Experience with star/snowflake schemas, fact/dimension modeling, and slowly changing dimensions
- Batch processing pipelines using Python and SQL