Data Engineer – Google Ad Manager Specialization
Vancouver
Fulltime
At Fastloop, we have a deep passion for helping businesses build their future. We use leading technologies and best-in class business expertise within our three core pillars of service excellence: Data, Analytics and AI (including Generative AI and Machine Learning).
As a boutique consultancy, our client engagements cover a broad spectrum of the modern data stack, leveraging platforms like Google Cloud to quickly and iteratively produce Analytics and AI outcomes for our clients.
Fastloop’s consulting model requires a team who is willing and able to work quickly, across new industries/verticals, with emerging technologies, in a fast, agile fashion. All team members must be extremely proactive, willing to explore the unknown and comfortable adapting to changing technical and functional requirements.
Fastloopers are technology and consulting experts who want to understand how our customers companies’ operate from the inside out. We are passionate about adding significant operational value, treating our clients' businesses as our own. We are problem solvers who like to roll up our sleeves and accelerate digital transformation journeys - always leveraging data as our foundation.
About the Opportunity:
The Data Engineer will be leading the integration and optimization of Google Ad Manager. This role will focus on supporting the set up of Google Ad Manager and also building the data infrastructure required to enable ad monetization, performance insights and connected retail experiences. They will work closely with marketing, ad operations, data and analytics and IT teams to integrate GAM and connect ad delivery and performance data with the broader Retail Media Network.
What you'll need to succeed:
Core Experience & Languages:
- 3+ years of data engineering experience, preferably in a retail or digital marketing environment.
- Expertise in SQL and Python for data manipulation, transformation, and orchestration.
Azure Platform:
- Proficiency in Azure Data Factory (ADF).
- Experience deploying and managing workflows in a cloud-native Azure environment (e.g., Azure Synapse Analytics, Azure Storage, Azure Key Vault).
- Experience with cost optimization strategies specific to Azure services.
Databricks Platform:
- Proficiency in Databricks (Spark, Delta Lake) and PySpark.
- Proficiency with Delta Live Tables (DLT) for declarative ETL.
- Experience using Unity Catalog for governance, lineage, and discovery.
- Experience creating and managing Databricks Workflows/Jobs.
- Familiarity with Databricks SQL for analytics users.
Data Engineering Practices:
- Data Modeling:
- Strong understanding of data warehousing concepts and dimensional modeling techniques (e.g., Star Schema, Snowflake Schema).
- Experience designing and implementing data models optimized for analytics within Delta Lake / Databricks.
- Data Ingestion & Handling:
- Experience working with various data formats (e.g., Parquet, Avro, JSON, XML).
- Experience building connectors or ingesting data from various REST APIs (including, but not limited to, Google Ad Manager).
- Data Quality & Testing:
- Experience implementing automated data testing frameworks (e.g., pytest, Great Expectations) within data pipelines.
- Experience developing comprehensive data quality rules and validation processes.
- Performance Tuning & Optimization:
- Advanced skills in optimizing Spark SQL queries and PySpark code (e.g., understanding partitioning, shuffle operations, broadcast joins, caching strategies).
- Skill in optimizing Databricks jobs (e.g., leveraging Photon engine).
- Experience with cost optimization strategies specific to Databricks.
Domain Specific (Marketing/Advertising):
- Strong experience working with Google Ad Manager (GAM) APIs and digital advertising data structures.
- Understanding of advertising performance metrics (CPM, fill rate, CTR, ROAS) in the context of retail media.
DevOps & Collaboration:
- Knowledge of Azure DevOps, Git, and CI/CD best practices in a data engineering context.
- Proven ability to collaborate effectively within a consulting team structure and communicate technical details clearly to both technical and non-technical stakeholders.
Nice-to-Haves:
- Experience with other Google Marketing Platform tools (DV360, Campaign Manager 360).
- Familiarity with retail media platforms and sponsored product campaign data.
- Certification in Microsoft Azure or Databricks.
Ready to join the team?
