Senior Data Engineer, Ads Data (AI Native) in Haciendas del Canada, Nuevo León at Jobgether

• 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.

• 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.

• Competitive compensation:

  • 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.

• Health and wellness:

  • Supplemental medical and dental coverage.

  • Life and disability insurance.

  • Mental wellness programs and Employee Assistance Program (EAP).

• Retirement and financial benefits:

  • Canadian RRSP and Deferred Profit Sharing Plan (DPSP).

• Work-life balance:

  • Flexible paid time off.

  • Company-wide holidays throughout the year.

  • Summer and winter company shutdowns.

  • Paid parental leave.

• Remote work and equipment:

  • Remote-first working environment across Canada.

  • Equipment, tools, and reimbursement support to create a productive home office.

• Professional development:

  • Learning and development programs.

  • Opportunities to work with cutting-edge data engineering and AI technologies.

• Additional perks:

  • 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.