Senior Platform Engineer helping design, scale, and harden Pivotal’s AI - driven platform. Collaborating closely with engineering teams to improve reliability, security, and scalability.
About the role
- Data Platform Engineer responsible for reviewing and stabilizing platform implementations at AVL Maroc SARL AU. Involves mentoring the development team and ensuring best practices in data engineering.
Responsibilities
- Review and stabilize existing platform implementations (Databricks, Foundry – pipelines, Ontology schemas, Workshop applications, Functions, notebooks).
- Identify performance bottlenecks, technical debt, and governance gaps across data pipelines and application layers.
- Lead Ontology governance and design reviews, acting as a gatekeeper for all schema changes (Object Types, Links, Properties, Actions).
- Define and document target data architectures (ingestion, transformation, and consumption layers).
- Establish coding standards, naming conventions, repository structures, and Function versioning policies.
- Enforce code reviews and technical validation before production deployment through Foundry Branching and Proposal workflows.
- Define and implement a structured testing strategy (unit tests for Functions, integration tests, data quality checks, pipeline expectations).
- Design and improve CI/CD pipelines and Dev/Test/Prod promotion processes using Foundry Marketplace/DevOps.
- Automate deployments, rollbacks, and environment configurations.
- Create and maintain architecture documentation (ADRs, data lineage diagrams, Ontology schemas, data flow diagrams).
- Design reusable Workshop component libraries, custom widgets, and Slate application patterns.
- Design and validate new platform solutions aligned with strategy, security, and governance requirements.
- Mentor the development team on architectural thinking and platform best practices (40% hands-on coding, 60% architecture/leadership).
Requirements
- Master’s degree in Computer Science, Data Engineering, or a related field.
- 5+ years of experience in data engineering or platform architecture roles.
- Strong expertise in modern data platforms (Databricks, Snowflake, AWS Glue, Azure Synapse, or similar).
- Foundry experience is strongly preferred but not required.
- Advanced skills in Python (PySpark), SQL (Spark SQL), and TypeScript for backend logic and application development.
- Experience with distributed data processing (Spark architecture, partitioning strategies, performance optimization).
- Strong understanding of relational databases (PostgreSQL, Oracle, or similar).
- Experience with CI/CD workflows, Git branching strategies, and automated testing in data environments.
- Solid experience in end-to-end ETL and data transformation processes.
- Proven experience in performance optimization and scalable architecture design.
- Experience in defining development standards, interface contracts, and engineering best practices.
- Hands-on coding mindset: must write production code daily, not only review or document.
- Structured, analytical, and documentation-oriented approach.
- Strong communication and technical leadership skills, with very good proficiency in English and French.
Benefits
- A competitive package and benefits
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