Technical Lead Data (Databricks)

TL;DR

Technical Lead Data (Lakehouse): Designing and evolving data foundations and scalable data architectures for hirify.global's Quality Foundations products with an accent on observability, performance, and AI integration. Focus on implementing Lakehouse platforms, optimizing high-volume data pipelines, and defining technical standards across multidisciplinary teams.

Location: Office-based in Montreal (Canada), Saint-Mandé or Paris (France), or Singapore (Singapore)

Company

hirify.global is a leading global game developer and publisher.

What you will do

• Collaborate with architects to design robust, scalable data products and services aligned with organizational needs.
• Act as the primary technical authority and subject matter expert for data architectures and processing pipelines.
• Define, maintain, and promote data standards and best practices through Architecture Decision Records (ADRs).
• Optimize the performance, cost-efficiency, reliability, and scalability of relational and non-relational database systems.
• Mentor data development teams to foster technical autonomy and knowledge sharing.
• Perform technical evaluations of new platforms and data-related approaches to improve the data ecosystem.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, or an equivalent field.
• Minimum 8 years of experience in software development or data engineering.
• Significant experience designing and implementing large-scale data platforms and distributed architectures.
• Strong proficiency in Python, PySpark, SQL, and Scala.
• Deep knowledge of Medallion architectures and Lakehouse platforms such as Databricks and Delta Lake.
• Proven experience in technical leadership, team coaching, and mentorship.

Nice to have

• Experience with cloud services (AWS, Azure), Docker, and Kubernetes.
• Knowledge of data orchestration frameworks like Apache Airflow or Databricks Workflows.
• Experience with real-time data streaming (Spark Structured Streaming).
• Proficiency with Elasticsearch/OpenSearch, SQL Server, and PostgreSQL.
• Understanding of machine learning and artificial intelligence concepts.
• Experience in high-volume, real-time critical systems environments.