Senior Data Engineer

• Design and build scalable cloud-native data platforms from greenfield to production
• Implement near-real-time ingestion pipelines using event-driven patterns
• Define and enforce platform standards including Data Lake / Lakehouse principles medallion architecture and data contracts
• Refactor and optimise existing Spark and PySpark scripts for performance and maintainability
• Introduce best practices for code quality testing and CI/CD across data pipelines
• Drive adoption of AI tooling and agentic workflows within the data engineering team
• Ensure data quality observability and reliability across all pipelines and platforms
• Develop self-service tooling and microservices to simplify platform usage for other teams

Qualifications :

• 5 years of professional experience in Data Engineering
• Strong Python and SQL development skills for pipeline development and optimisation
• Proficiency in Apache Spark / PySpark including query optimisation and performance tuning
• Hands-on experience with Databricks (preferred) or Snowflake
• Experience with at least one major cloud provider: Azure (preferred) AWS or GCP
• Experience with stream processing technologies (Kafka Spark Structured Streaming)
• Solid understanding of ETL/ELT patterns data modelling (dimensional Data Vault) and data warehousing
• Experience with orchestration tools (Apache Airflow Azure Data Factory or equivalent)
• Knowledge of Infrastructure as Code (Terraform or equivalent)
• Understanding of production-grade system requirements: reliability scalability observability and performance
• Upper-Intermediate English level

WILL BE A PLUS

• Familiarity with RAG pipeline design and LLM integration patterns
• Knowledge of data governance frameworks and tools (Unity Catalog Apache Atlas or similar)
• Experience with dbt for data transformation and modelling
• Familiarity with MLflow Feature Stores or ML platform integration

Additional Information :

PERSONAL PROFILE

• Self-driven and proactive in identifying improvements
• Comfortable working in a fast-paced innovative environment
• Strong problem-solving mindset with attention to detail
• Open to experimenting with emerging technologies and approaches

Remote Work :

Yes

Employment Type :

Full-time