Intermediate Data Engineer

Clever Digital Marketing

. Build and maintain production ELT pipelines ingesting data from Google Ads, Meta Ads, Microsoft/Bing Ads APIs, CRM, call tracking, and lead event sources into BigQuery .

Posted 11/6/2026full-timeCanadaJuniorMid-Level💰 CA$90,000 - CA$120,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining ELT pipelines, integrating third-party APIs, and developing BigQuery data models. Proficient in SQL and Python automation, with a solid understanding of data warehousing fundamentals and performance optimization.

Highest-signal resume keywords

SQL ProficiencyPython AutomationBigQuery ExperienceAPI IntegrationData Warehousing Fundamentals

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonBigQueryData ModelingAPI IntegrationData TransformationAutomationVersion ControlPerformance TuningQuality Checks

Tools & Technologies

Cloud RunCloud FunctionsPub/SubDataformGit

Industry Keywords

ELT PipelinesData EngineeringAnalytics EngineeringPrivacy-Compliant MeasurementPerformance Marketing

Tech Stack

Tools & technologies

Amazon RedshiftBigQueryCloudGoogle Cloud PlatformPythonSnowflakeSQL

About the role

Key responsibilities & impact

Build and maintain production ELT pipelines ingesting data from Google Ads, Meta Ads, Microsoft/Bing Ads APIs, CRM, call tracking, and lead event sources into BigQuery
Own reliable Bronze-layer ingestion with audit trails and no silent failures
Extend and maintain REST/OAuth2 API connectors within Cloud Run patterns and troubleshoot integration issues to root cause
Implement Silver-layer transformations and contribute Gold-layer Dataform models
Raise architecture gaps, risks, and improvement opportunities with proposed approaches
Contribute to CDMID join logic unifying CRM, ad platform, and call-tracking data
Develop and maintain BigQuery data models using dimensional modeling fundamentals
Write SQL and Python automation using Cloud Run, Cloud Functions, and Pub/Sub
Monitor and tune pipelines and BigQuery queries for performance and cost efficiency
Help replace low-code automation with reliable, auditable pipelines
Implement quality checks, validation, testing, and documentation
Monitor pipeline health and resolve root causes of data discrepancies
Handle lead and client data responsibly using consent boundaries and least-privilege access

Requirements

What you’ll need

2–4 years of hands-on data engineering or analytics engineering experience with real production contributions
Strong SQL and working Python proficiency
Hands-on experience with BigQuery or an equivalent cloud data warehouse (Snowflake, Redshift)
Practical experience integrating third-party APIs (REST, OAuth2) into data workflows
Working experience with at least part of the GCP stack, or strong equivalent cloud experience and ability to ramp quickly
Solid grasp of data warehousing fundamentals: staging vs. modeled layers, incremental loads, deduplication, and idempotent design
Version control (Git) and code review as daily working habits
Direct experience with a major ad platform API, Dataform/dbt/SQLMesh, Pub/Sub, performance marketing, CRM pipelines, low-code automation replacement, or privacy-compliant measurement are nice to have
Candidates must be legally eligible to work in Canada

Benefits

Comp & perks

An incredible team and culture — high-performance, feedback-oriented, and data-driven, where everyone is empowered to succeed
Real ownership of production systems within a platform being built from the ground up
Be part of the #1 fastest-growing marketing company in Canada
A modern, GCP-native stack with AI embedded in daily workflows
Exposure to AI/NLQ, MMM modeling, and ML optimization layers
Fully remote work environment with the flexibility to work from anywhere in Canada
3+ weeks of paid time off annually
Comprehensive group benefits including health, dental, and vision
Company-provided MacBook Pro and home office budget
A work abroad policy
Merch deliveries and opportunities to connect with teammates at meetups and company-wide events
Defined growth path toward Senior Data Engineer
Occasional in-office collaboration opportunities