Senior Data Engineer, Ads Data (AI Native)

Jobgether; Canada; Remote; CAD 150,000 - 178,000; Full time

Benefits offered by this job

RSUs

Medical and dental coverage

Life and disability insurance

EAP

RRSP / DPSP

Flexible paid time off

Remote-first across Canada

Job summary

Jobgether, on behalf of a partner, is seeking a Senior Data Engineer (Ads Data, AI Native) based in Canada. This remote-first role focuses on building scalable data infrastructure for advertising analytics, campaign performance, and BI across a collaborative, international team.

You will own critical data pipelines, enhance reliability and cost efficiency, and apply AI-native practices to accelerate development and debugging. Strong cross-functional collaboration is essential.

Qualifications

• 5+ years of professional data engineering experience building production-scale data platforms.
• Proficient in Spark (PySpark/Scala) with partitioning and performance optimization.
• Deep Databricks knowledge (Delta Lake, Unity Catalog, Jobs/Workflows, SQL Warehouses).
• Strong SQL and Python/Scala for pipelines, automation, and queries.
• Hands-on with dbt, CI/CD, and data quality/tests.

Responsibilities

• Develop and optimize data infrastructure including batch and streaming pipelines and Delta Lake tables using Databricks.
• Collaborate with analysts, strategists, and sales to deliver reliable datasets and actionable insights.
• Maintain dbt models, tests, semantic layers, and standardized metrics for consistency.
• Improve Spark/Databricks performance and resource usage.
• Manage cloud infrastructure with Terraform and AWS (S3/IAM).
• Enforce data governance, lineage, SLAs, and privacy/compliance controls.
• Lead engineering best practices, CI/CD, testing, and documentation; mentor peers.
• Integrate data from ads platforms, CRM, partners, and migrations from legacy tools.
• Leverage AI-native practices and tools to accelerate development and code quality.

Skills

Spark

SQL

Python/Scala

Data modelling

AI tooling

CI/CD

Airflow/Databricks Workflows

AWS

Delta Lake

Partitions & performance

Education

Bachelor's degree in CS/Engineering

Tools

Databricks

dbt

Terraform

AWS S3/IAM

Git

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer, Ads Data (AI Native) based in Canada.

Join a remote-first technology organization building innovative products that help families stay connected and protected. As a Senior Data Engineer, you will play a key role in developing and scaling the data infrastructure that powers advertising analytics, campaign performance, and business intelligence. You will take ownership of critical data pipelines and platforms, improving their reliability, scalability, performance, and cost efficiency. Working closely with analysts, advertising strategists, and commercial teams, you will transform complex datasets into trusted, actionable insights. You will also embrace AI-native engineering practices, leveraging advanced AI tools to accelerate development, improve productivity, and strengthen technical capabilities. This is an opportunity to combine hands-on engineering, technical leadership, and business impact within a highly collaborative international environment.

Accountabilities

• Develop and optimize data infrastructure: Enhance, maintain, and scale existing batch and streaming pipelines, Delta Lake tables, and data workflows using Databricks.
• Build business-focused data solutions: Collaborate with analysts, advertising strategists, and sales teams to transform business requirements into reliable datasets, reporting solutions, and actionable insights.
• Manage data models and metrics: Develop and maintain dbt models, automated tests, semantic layers, and standardized business metrics to ensure consistency and accuracy across teams.
• Optimize performance and costs: Improve Spark and Databricks workloads through query optimization, partitioning, cluster configuration, and efficient resource allocation.
• Manage cloud infrastructure: Maintain data platform infrastructure using Terraform and AWS, ensuring scalable, secure, and reliable operations.
• Strengthen data quality and governance: Implement monitoring, data lineage, SLAs, alerting, access controls, and data contracts while ensuring compliance with privacy and regulatory requirements.
• Lead engineering excellence: Establish best practices for version control, CI/CD, testing, documentation, and code reviews while mentoring colleagues and contributing to technical roadmap decisions.
• Integrate diverse data sources: Consolidate and reconcile information from advertising platforms, CRM systems, external partners, and internal applications, including migrations from legacy reporting tools.
• Advance AI-native engineering: Develop tools, workflows, and AI agents that provide LLMs with relevant context and accelerate development, debugging, and system maintenance.
• Drive continuous improvement: Take ownership of foundational data pipelines and models, reduce processing times and infrastructure spending, and increase self-service access to reliable business information.

Requirements

• At least 5 years of professional data engineering experience building and maintaining production-Grade data platforms at enterprise scale.
• Advanced hands-on expertise in Apache Spark, including PySpark or Scala, with strong knowledge of partitioning, joins, shuffle behavior, caching, skew management, and performance optimization.
• Deep knowledge of Databricks, including Delta Lake, Unity Catalog, Jobs and Workflows, Databricks Asset Bundles, Structured Streaming, and SQL Warehouses.
• Strong proficiency in SQL and Python or Scala for data pipeline development, automation, and query optimization.
• Practical experience with dbt, including data modeling, incremental strategies, testing, documentation, and CI/CD integration.
• Hands-on experience with Terraform and AWS, particularly S3, IAM, and cloud infrastructure fundamentals.
• Experience with orchestration technologies such as Airflow or Databricks Workflows, Git, CI/CD pipelines, and production monitoring.
• Strong understanding of data architecture and modeling principles, including dimensional modeling, star schemas, medallion architecture, and semantic layers.
• Demonstrated ability to improve existing pipelines and data models while maintaining reliability, scalability, maintainability, and backward compatibility.
• Experience using AI coding assistants such as Claude, Cursor, or GitHub Copilot for substantive engineering tasks, with the ability to review, test, and take full ownership of AI-generated code.
• Strong analytical and problem-solving skills, with the ability to translate complex business requirements into effective technical solutions.
• Excellent communication and collaboration skills, particularly when working with non-technical stakeholders and cross-functional teams.
• Familiarity with data governance, privacy, and compliance standards, including GDPR, CCPA, and SOX.
• Experience with business intelligence platforms such as Domo, Tableau, or Looker is an advantage.
• Previous experience in advertising technology, media data, campaign performance, audience analytics, attribution, or revenue reporting is highly desirable.
• A bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent professional experience.

AI-Native Engineering Expectations:

• Regular use of AI coding assistants for development, analysis, refactoring, testing, documentation, and codebase navigation.
• Strong technical judgment to validate AI-generated outputs and maintain high standards for code quality, security, and reliability.
• Ability to use AI tools to increase engineering productivity and independently tackle complex technical challenges.
• Willingness to share effective AI workflows, support colleagues in adopting new tools, and contribute to continuous improvements in engineering practices.
• Curiosity and adaptability to stay current with evolving AI technologies and recommend tools that improve team performance.

Benefits

• Annual base salary range for Canada: $149,500–$177,500 CAD.
• Additional equity compensation through Restricted Stock Units (RSUs).
• Comprehensive total rewards package, with final compensation determined by experience, skills, and geographic location.
• Supplemental medical and dental coverage.
• Life and disability insurance.
• Mental wellness programs and Employee Assistance Program (EAP).
• Canadian RRSP and Deferred Profit Sharing Plan (DPSP).
• Flexible paid time off.
• Company-wide holidays throughout the year.
• Summer and winter company shutdowns.
• Paid parental leave.
• Remote-first working environment across Canada.
• Equipment, tools, and reimbursement support to create a productive home office.
• Learning and development programs.
• Opportunities to work with cutting-edge data engineering and AI technologies.
• Complimentary premium membership to the company's family safety platform.
• Complimentary Tile tracking devices.
• Inclusive culture: A collaborative, mission-driven environment that values integrity, respectful communication, innovation, and meaningful impact.