Data Engineer with AWS

What you'll be doing

• Develop and maintain data pipelines:
• Modify existing Lambda functions, SQL queries and processing jobs to add new features
• Refactor code to ingest/process external data
• Add quality checks to existing pipelinesDesign and optimize data models:
• Design data models leveraging Iceberg format, for “silver” and “gold” layers
• Optimize queries for performanceEnsure data quality and governance:
• Apply data validation rules
• Build automated quality checksDocumentation and knowledge sharing:
• Document the data preparation process clearly, including transformations, code comments, and key decisions
• Store all code in GitLab with meaningful commit messages and proper versioning for code and datasets

What we're looking for

• Data Engineering Design and Delivery
• 4–6 years of experience as Data Engineer
• Proven experience designing and building scalable, reliable, and maintainable data pipelines.
• Familiarity with CI/CD, automated testing, and Infrastructure as Code practices.
• Strong Python-based data pipeline development skills (or equivalent), with experience applying Test-Driven Development and AI-assisted coding practices.
• Strong data modeling and schema design expertise, including analytical models and scalable, maintainable data structures.
• Familiarity with DBT (Core or Cloud), including modular SQL transformations, data modeling, testing, documentation, and dependency management.Orchestration, Quality, and Reliability
• Familiarity with pipeline orchestration tools such as Airflow.
• Understanding of data observability, monitoring, failure recovery, and pipeline reliability.Cloud and Performance Optimization
• Strong SQL expertise, including complex queries, performance optimization, and analytical data modeling.
• Knowledge of optimizing Iceberg tables, Athena queries, and Spark workloads for performance and cost efficiency.
• Hands-on experience with AWS services, including Athena, Lambda, Aurora, EventBridge, Glue, and SageMaker.Soft skills
• Clear, concise communication with engineers, product, and data stakeholders.
• Pragmatic mindset: balances engineering rigor with delivery.
• Sense of ownership
• Fluent English

We offer

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