We are At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 17,000+, and has 58 offices in 22 countries within key global markets.

Our challenge Seeking a motivated, proactive, and reliable Data Engineer to join the Data Sourcing and Analytics team. This role will support the design, development, implementation, and ongoing enhancement of enterprise data solutions across cloud data platforms. The ideal candidate will bring strong SQL programming, Snowflake, Databricks, Spark, and Python development experience, along with the ability to analyze business requirements, translate them into scalable data solutions, and collaborate effectively with technology and business stakeholders. Experience in the finance or banking domain is a strong plus.

Additional Information

The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within Mississauga,



ON is CAD $115k – CAD $130k/year & benefits (see below).

Role Responsibilities

Design, develop, and maintain scalable enterprise data warehouse, data lake, and cloud-based data engineering solutions. Develop robust ETL/ELT pipelines and transformation routines using SQL, Snowflake, Databricks, Spark, Python, and related cloud data platform services. Write, optimize, and troubleshoot complex SQL queries, stored procedures, and data transformation logic for large and complex datasets. Create and maintain data mappings, source-to-target specifications, data lineage documentation, and transformation rules to support enterprise reporting and analytics needs. Perform analysis and interpretation of business, functional, and technical requirements, and translate requirements into reliable data engineering designs. Partner with business analysts, data architects, application teams, and reporting teams to understand data needs and deliver high-quality data solutions. Support data modeling efforts, including dimensional modeling, fact and dimension design, data normalization, and fit-for-purpose analytical structures. Perform testing, validation, reconciliation, performance tuning, and production support for data pipelines and analytical datasets. Use modern engineering practices and productivity tools, including GitHub Copilot or similar AI-assisted development capabilities,



to improve development efficiency and code quality. Contribute to cloud data platform migration, modernization, and operational support initiatives across the enterprise data ecosystem.

Requirements

- 5+ years of experience in enterprise data management, data engineering, data warehousing, or large-scale data platform development.
- Strong SQL programming experience, including development of complex queries, stored procedures, performance tuning, data profiling, and reverse engineering of existing data processes.
- Hands‑on experience with Snowflake development and utilities such as SnowSQL, time travel, metadata management, data sharing, and query optimization.
- Hands‑on experience with Databricks and Spark programming for large-scale distributed data processing, transformations, and analytical workloads.
- Strong Python programming experience for data processing, automation, API integration, scripting, and pipeline development.
- Experience with data modeling concepts, including OLTP, OLAP, dimensional modeling, facts, dimensions, and enterprise analytical data structures.
- Experience creating data mappings, source-to-target specifications, transformation logic, and documentation to support downstream reporting and analytics.
- Ability to analyze and understand business, functional, and technical requirements and convert them into scalable, maintainable data solutions.
- Working knowledge of cloud-based data architecture, messaging patterns, analytics platforms, and contemporary data engineering design principles.
- Experience supporting testing, validation, reconciliation, defect resolution, deployment, and production support for enterprise data solutions.
- Familiarity with

📌 Senior Data Engineer – Capital Markets (Mississauga)
🏢 Synechron Canada ULC_CANADA
📍 Mississauga