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Data & Analytics Engineer

Job in Toronto, Ontario, M5A, Canada
Listing for: Prophix
Full Time position
Listed on 2026-08-06
Job specializations:
  • Software Development
    Data Engineering
Job Description & How to Apply Below

See what you can do with Prophix

At Prophix, we’re building the platform that helps finance teams stop managing spreadsheets and start driving strategy. Prophix One™ brings planning, reporting, consolidation, and automation together in a single place, and we are expanding its AI capabilities faster than ever. If you want to work on a product that genuinely changes how finance teams operate, and do it alongside people who care about getting it right, this is where you want to be.

We’re headquartered in the Greater Toronto Area, with teams and offices across North America, Europe, and Australia. Trusted by more than 3,000 finance teams across 100+ countries, Prophix One™ is built for organizations that want to plan smarter and move faster.

Prophix is building a data platform on Snowflake that drives revenue, customer success, finance, and executive decision-making. Data infrastructure, AI, and business strategy are all moving at the same time here, and this role sits at the center of that. It is not a steady-state job.

You will own the pipelines and integrations that move data from Salesforce, Gong, Churn Zero, Pendo, Eloqua, and Demandbase into Snowflake, and the platform architecture that keeps that data clean, fast, and ready for AI. You take ownership of outcomes, not just tasks, and you build for the next engineer as much as yourself. You work directly with the Director of Revenue Operations & Analytics and alongside Analytics Engineers, and senior business stakeholders, and you can make sense to all of them.

If you know Snowflake well, think in systems, and want to build data infrastructure that shows up in board-level reporting and agentic workflows, this role is worth a conversation

What You Will Do

Snowflake Platform Engineering

  • Work across the Snowflake platform with real depth: multi-cluster warehouse configuration, resource monitors, query profiling, materialized views, Dynamic Tables, and Snowpark-based compute patterns. You will grow into full ownership of this layer
  • Design and optimize schemas using star and snowflake dimensional models; govern clustering keys, search optimization, and micro-partition pruning strategies for large-scale analytical workloads
  • Implement and manage Snowflake security architecture: RBAC, row-level and column-level security policies, data masking policies, and network policies
  • Build incremental pipelines using Snowflake-native Streams, Tasks, and Dynamic Tables, keeping logic inside the warehouse and removing the need for external scheduling tools
  • Drive cost governance through virtual warehouse right-sizing, auto-suspend/resume configuration, result cache optimization, and credit consumption monitoring
  • Manage environment lifecycle across dev, staging, and production using zero-copy cloning, time travel, data sharing, and failsafe strategies

Pipeline & Integration Engineering

  • Design and maintain production-grade ELT pipelines from Salesforce (SOQL, Bulk API, CDC), Gong, Churn Zero, Pendo, Eloqua, and Demandbase into Snowflake using Python and AWS-native tooling (Lambda, Glue, S3)
  • Build REST API connectors and integration frameworks with retry logic, idempotency, dead-letter queue patterns, and schema drift handling so pipelines do not fall over when source systems change
  • Treat data infrastructure like software: automated testing, peer code review, and a clear promotion path from development through staging to production. Nothing goes live without passing those checks.
  • Own pipeline monitoring: SLA tracking, alerting, data lineage documentation, and incident resolution with a clear root cause every time

AI-Enabled Data Engineering

  • Build the data foundations that AI runs on: feature stores, embedding pipelines, and clean gold-layer datasets that LLM and agentic workflows can actually use
  • Use Snowflake Cortex LLM functions (COMPLETE, SUMMARIZE, SENTIMENT, ) to enrich operational data inside the warehouse, so you are not making unnecessary round-trips to external AI APIs
  • Build Cortex Search and Cortex Analyst integrations so business users can query Snowflake data in plain English without needing to write SQL
  • Build agentic data pipelines using Snowflake Notebooks and Snowpark…
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