Data Engineer

Data Engineer
Department:
Data & EngineeringEmployment Type:
Full TimeLocation:
CanadaCompensation:
CA$90,000
- CA$120,000 / yearDescription
RoleData EngineerWho We AreMission : At Clever Digital Marketing, we are on a mission to empower large-scale home improvement companies by fueling their top-line revenue through innovative digital marketing strategies. By bridging the gap in the industry for a highly profitable digital lead vendor, we've created a unique space where growth isn't just supported — it's catalyzed.
Product : Clever Digital Marketing delivers outcome-driven paid advertising and strategic advising solutions. We don't focus on clicks and impressions — we focus on net sales. Our customized, data-driven strategies are tailored to each client's unique needs, ensuring measurable impact and scalable profitability across Google, Meta, and Microsoft ad platforms.
Scale : Recognized by the Globe and Mail as the #1 Fastest-Growing Company in the Marketing & Advertising category and #42 across all of Canada, we are the growth engine behind some of North America's most ambitious home improvement brands — companies on track to generate over $500 million in combined revenue in 2026. With a team of 80+ across North America, $74M in digital ad spend managed, and 400,000+ leads generated, we've built something rare: a system where scale isn't luck. It's engineering.
Impact : As trusted subject matter experts in the home improvement space, we are redefining what it means to deliver value. Our commitment to authenticity, collaboration, and continuous improvement ensures we remain a powerhouse of growth and measurable results for every client we serve. We don't do lead generation — we do revenue generation.
Who We Are Looking ForWe are looking for an Intermediate Data Engineer to build and strengthen the pipelines that power our entire advertising operation. As we scale Data Platform 2.0 — our GCP-native data platform — we need an engineer who delivers reliable, well-tested work independently, takes real ownership of defined portions of the stack, and is hungry to grow into broader platform ownership alongside a senior team. You won't be designing the architecture on day one — but you will be trusted to build within it, improve it, and prove you're ready for more.

Key Responsibilities

What You’ll DoBuild and Manage Data PipelinesBuild and maintain production ELT pipelines ingesting data from Google Ads, Meta Ads, and Microsoft/Bing Ads APIs — as well as CRM, call tracking, and lead event sources — into our BigQuery data ecosystemOwn reliable Bronze layer ingestion for your assigned sources, with audit trails and no silent failuresExtend and maintain API connectors (REST/OAuth2) within our established Cloud Run patterns, and troubleshoot integration issues to root cause rather than working around themDeliver Within the Platform ArchitectureImplement Silver layer transformation logic and contribute Gold layer Dataform models serving Command Centre, client reporting, and future AI/ML consumers — working from designs set by the Data Team leadershipRaise gaps, risks, and improvement opportunities in the architecture proactively — bring a proposed approach, not just the problemContribute to the CDMID join logic that unifies CRM, ad platform, and call tracking data into coherent lead records across client accountsManage Data Warehousing and ModelingDevelop and maintain BigQuery data models for your assigned domains, applying dimensional modeling fundamentals with consistent naming, structure, and documentationDeliver clean, trusted, cost-metric-driven datasets that let our team move beyond vanity metrics to cost-per-issued-lead and cost-per-demo insightsAutomate and OptimizeWrite SQL & Python-based automation using GCP services — Cloud Run, Cloud Functions, and Pub/Sub — to orchestrate workflows and eliminate manual processesMonitor and tune pipelines and BigQuery queries for performance and cost-efficiency, flagging systemic issues before they compoundHelp graduate workflows off low-code automation tools and onto reliable, auditable pipelinesOwn Data Quality, Documentation and Responsible Data HandlingImplement quality checks and validation on everything you ship — and treat testing & documentation as part of delivery, not an afterthoughtProactively monitor pipeline health and resolve the root causes of data discrepancies, not just flag themHandle lead and client data responsibly: respect consent boundaries, follow least-privilege access practices, and avoid introducing PII where it is not neededSkills, Knowledge and Expertise
What We Are Looking ForNon-Negotiables2–4 years of hands-on data engineering or analytics engineering experience with real production contributions — you've built and maintained pipelines that other people depended onStrong SQL and working Python proficiency for data transformation, scripting, and pipeline developmentHands-on experience with BigQuery or an equ