Analytics Data Engineer – Treasury/FinanceDuration: 6 monthsExtension Potential: NoFTE Conversion: NoWork Hours: 9:00 AM – 5:00 PMLocation: Remote or Hybrid (must be able to visit the office for technical issues or special occasions)Key ResponsibilitiesData 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 effective 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 & Tools8-10 years of strong experience in Python, SAS, and SQLPower BI, DAX, and M Code for dashboard developmentProficiency in MS 365 Suite: Office, Power Automate, SharePoint, OneDriveAdvanced SQL Server configuration for high-throughput analytics (memory allocation, parallel query execution)Experience with partitioned tables, indexed views, and columnstore indexesDeep understanding of SQL Server recovery models, backup/restore strategies, and disaster recovery planningDesign and implementation of ETL pipelines with incremental loads and change data captureData staging and processing large-scale datasets efficientlyExperience with star/snowflake schemas, fact/dimension modeling, and slowly changing dimensionsBatch processing pipelines using Python and SQLKnowledge of RDBMS, NoSQL, and data file formats (CSV, Parquet, JSON)Translate business requirements into scalable, optimized data modelsStrong experience with AWS (Redshift, Glue, MLOps)Nice-to-Have SkillsReferrals increase your chances of interviewing at Swoon by 2xGet notified about new Data Engineer jobs in Toronto, Ontario, Canada.#J-18808-Ljbffr
📌 Senior Data Engineer (Toronto)
🏢 Swoon
📍 Toronto