🚀 Job Opportunity: Lead Databricks Architect (Global Food Corporation)

Are you a hands-on technical leader ready to shape the future of enterprise data and AI? ️ We are seeking a highly experienced Databricks Architect to lead the design, implementation, and optimization of enterprise-grade data platforms and AI-enabled workloads for a world-renowned global food corporation.

If you combine deep Databricks expertise with strong architectural leadership and thrive in a dynamic, managed service delivery model, we want to hear from you! ✨

Role Overview & Project Description

In this role, you will act as a trusted advisor and technical heavyweight. You will translate complex business and data requirements into scalable, Databricks-based solutions while ensuring robust governance, peak performance, and operational resilience.

Key Responsibilities

• Architect & Design: Lead the architecture and implementation of Databricks-based data platforms, pipelines, and AI/ML workloads ️.
• Define Lakehouse Patterns: Establish scalable patterns using core capabilities like Apache Spark, Delta Lake, Databricks SQL, MLflow , and governance components .
• Pipeline Engineering: Design robust batch and streaming data pipelines for high-volume, business-critical workloads .
• Standards & Optimization: Define architecture standards for performance tuning, workload orchestration, reliability, observability, and cost control ⏱️.
• Blueprints & Roadmaps: Translate business and technical needs into solution blueprints and execution roadmaps ️.
• Cross-Functional Collaboration: Team up with data engineers, analysts, data scientists, DevOps, and business stakeholders to deliver seamless end-to-end solutions .
• Governance & Security: Ensure rock-solid data governance, security, and compliance across the Databricks environment .
• AI Foundations: Support advanced analytics by enabling reliable feature engineering, model lifecycle practices, and production-ready data foundations .
• Technical Leadership: Provide hands-on guidance during delivery, troubleshooting, and optimization of existing workloads .

️ Mandatory Skills & Qualifications

• Databricks Expertise: Deep, hands-on mastery of the Databricks platform (workspace design, cluster strategy, jobs orchestration, and platform optimization) .
• Apache Spark: Strong command of Spark and distributed data processing concepts, including performance tuning ⚡.
• Lakehouse Architecture: Proven experience designing and delivering enterprise data solutions using Delta Lake principles .
• Languages: Strong proficiency in Python and SQL (Scala is a definite plus!) .
• ETL/ELT Pipelines: Demonstrated capability in building/optimizing large-scale ingestion frameworks and data models .
• AI/ML Support: Experience supporting workloads via MLflow , managing model lifecycles, and setting up production-ready data .
• Cloud Platforms: Solid knowledge of cloud-native architecture patterns on AWS, Azure, or GCP (including storage, networking, and identity integration) ☁️.
• Data Governance: Experience with access control, data lineage, and compliance frameworks in enterprise environments ️.
• DevOps & CI/CD: Familiarity with infrastructure-as-code, monitoring, and operational best practices for data platforms .
• Problem Solver: Ability to dive into deep technical problem-solving with minimal ramp-up time .