Senior Data Engineer

Toronto, ON
On-site
Posted Oct 9, 2026
1 position

Opens LinkedIn

Employment type: Contract
Experience level: Senior · 5+ years
Posting language: English
Working hours: 40 hours per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Independently design and deliver cloud-native data solutions, backend services, RESTful APIs, and data pipelines, owning timelines, scope, dependencies, and execution risks. Ensure production readiness through testing, documentation, CI/CD, and handover while proactively communicating progress, trade-offs, and risks to stakeholders.

Job details

Project Description: We are seeking a hands-on Data Engineer to support the Total Fund Management Portfolio Management Technology team. This role focuses on implementing reliable data solutions in a cloud-native environment using established platform tooling and patterns. You are expected to independently design and deliver data solutions with minimal oversight. This is not a role for someone who requires detailed task breakdowns or constant direction. Once objectives and constraints are clear, you are expected to independently drive work to completion, proactively manage risks, communicate progress and trade-offs effectively, and manage stakeholder expectations. Responsibilities: Own timelines and deliverables, proactively managing scope, dependencies, and execution risks Independently frame, design, and deliver software solutions by engaging stakeholders, clarifying ambiguous requirements, and challenging assumptions Build backend services and RESTful APIs aligned to those designs Develop cloud-native applications (AWS preferred) Implement workflow automation and data pipelines where needed Contribute across the full software development lifecycle, including CI/CD Ensure solutions are production-ready, including testing, documentation, and handover Act as a reliable execution partner, proactively communicating progress, trade-offs, risks, and changes in expectations Mandatory Skills Description: Strong Python with PySpark Hands-on experience with Databricks, including developing and operating data workloads Schema design and data modelling experience Working knowledge of Spark sufficient to build and troubleshoot PySpark workloads; deep Spark specialization is not required Prior consulting, advisory, or client-facing delivery experience Proven ownership and independent delivery without close supervision Strong problem-solving skills, including the ability to frame and solve problems in ambiguous situations Strong communication and stakeholder management skills, including proactive expectation management Demonstrated adoption of AI-assisted engineering tools and practices as part of day-to-day engineering delivery Nice-to-Have Skills Description: Experience with Apache Iceberg · AWS data services (Glue, Lake Formation) · Workflow orchestration tools (Airflow) · Experience with distributed data processing architectures · Capital markets experience Languages: English: C1 Advanced

What you’ll do

Requirements

Requires strong Python and PySpark skills, hands-on Databricks experience, data modeling and schema design knowledge, and working knowledge of Spark. Candidates must demonstrate independent delivery, problem-solving in ambiguous situations, client-facing experience, strong communication and stakeholder management, and adoption of AI-assisted engineering tools.