Summary
✨ AI‑Generated
Join a six-month data engineering engagement with strong potential for extension, building cloud-based data products that support the full customer lifecycle. You will develop pipelines and single-source-of-truth datasets, use AI-assisted tools for development and analysis, validate generated SQL and code, protect sensitive information, and collaborate with marketing, product, sales, and data teams.
Highlights
Build end-to-end data solutions and trusted data products using cloud data technologies. The six-month engagement has a high possibility of extension and combines data engineering with AI-assisted development, exploratory analytics, responsible AI practices, and cross-functional collaboration.
Description
Data Engineer GCP
Duration: 6 months to start (high possibility for extensions)
Location: Toronto, ON (hybrid, 1 day a week)
What you will do
● Lead the development of new data solutions supporting the end-to-end customer journey, from Sales submission to Billing.
● Build data products that serve as the single source of truth for B2B performance reporting and marketing activity.
● Use Claude and MCP-connected tools to accelerate pipeline development, code generation, testing, documentation, and code/data audits.
● Apply AI-assisted data mining and exploratory analysis to uncover new data pipelines, value chains, and revenue, churn, and cross-sell opportunities.
● Define guardrails for responsible AI use: validating AI-generated SQL and code, protecting sensitive data, and maintaining auditability.
● Collaborate with stakeholders across marketing, product, sales, and data engineering.
● Build trust in our data products across the organization.
● Provide regular updates on KPIs, programs, and new solutions to leadership and stakeholders.
● Mentor junior team members, including coaching them on effective, responsible AI-assisted development.
What you bring
● 4+ years of experience leading large projects with multiple stakeholder groups.
● Experience with cloud platforms (GCP BigQuery preferred) and cloud-native technologies.
● Strong SQL skills and experience with databases such as Oracle or SQL Server.
● Hands-on experience using generative AI tools (Claude, Copilot, or similar) in data engineering workflows, with sound judgment on when to trust, verify, or override AI output.
● Familiarity with prompt design and AI agent concepts; experience with MCP, APIs, or tool integrations is an asset.
● Proven ability to answer business questions with data, define business outcomes, and manage stakeholder expectations.
● Excellent analytical skills, comfort with data ambiguity, and a passion for metrics.
● A love for exploring quantitative and qualitative data.
● Commitment to continuous learning in telco, technology, AI, and customer experience.
● Strong planning, performance, and business analysis skills.
● A desire to be part of a high-performing team that celebrates successes and shares learnings.
● A bachelor's degree in Engineering, Statistics, Computer Science, or a related field.
