Design and manage scalable data pipeline architectures for ingestion, transformation, and curation workflows
Build and maintain cloud-native data solutions using AWS technologies
Assemble and optimize large-scale datasets that support both functional and non-functional business requirements
Develop ETL pipelines using Python, SQL, PySpark, and modern big data technologies
Implement scalable infrastructure for extracting and processing data from multiple sources
Build analytics-enablement tooling that provides actionable business insights
Work closely with technical and business stakeholders to ensure data is accessible, reliable, and production-ready
Contribute to improving data quality, operational efficiency, and platform scalability

Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience
5+ years of experience as a Data Engineer or Software Engineer
Experience building cloud-native data platforms and pipelines
Strong hands-on experience with Python and SQL
Experience with PySpark or Apache Spark ecosystems
Strong ETL and data transformation experience
Experience with CI/CD pipelines and infrastructure automation
Strong knowledge of AWS services such as: S3, Athena, Lambda, Glue, IAM, SQS
Strong analytical and communication skills
Fluent English communication skills

Data Platform Engineer – AWS

Key skills