software engineer

Overview

Location Address : Hybrid - 44 King Street W 19th Floor, Toronto – 4 / week

Subject to change : 3–4 days onsite may be required based on business needs

Contract Duration : ASAP to Oct 31, 2026 – approx. 7 months

Possibility of extension & conversion to FTE

Schedule Hours : 9am-5pm Monday-Friday; standard 37.5 hrs / week

Story Behind the Need

Business group : Data Models & Analytics – the primary technology group supporting all financial functions within the CFO organization. This includes financial forecasting, planning and analysis, budgeting, treasury, performance data, and any technology solutions required by Finance. The group is an internal-facing technology team of ~300 people. Immediate team they will be working with is 6 total (others on the team are software engineers).

Responsibilities

• Integrate new data pipelines from various source systems into the FP&A platform to enable its use as a core forecasting and budgeting tool.
• Build and enhance the integration engine / platform that ingests data from multiple sources.
• Apply best-practice software engineering principles throughout development.
• Contribute to the development of a full-scale data-driven application that will continue to expand as new data sources are onboarded.
• Work closely with Business Analysts and end users to translate business requirements into technical logic for data handling.
• Analyze financial data and work directly with databases.
• Role breakdown : 80% coding / 20% requirements gathering and stakeholder interaction.
• Technical Stack - Languages : Python, Apache Airflow; Platforms : Anaplan, Cloud Composer; Cloud : GCP; Infrastructure : Kubernetes; Databases : SQL, SQL Server, Postgres

Candidate Value Proposition

Qualifications

Nice-To-Have Skills

Education

Best vs. Average Candidate

The strongest candidates will have experience supporting or integrating data into FP&A platforms such as Anaplan or Hyperion, combined with strong Python development skills. Additional experience building applications from scratch—whether in Python, Java, C++, or similar languages—is highly valued. A strong data-centric mindset and experience processing large datasets efficiently will stand out.

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