Principal Data Engineer

Experteer Overview In this role you will design and operate scalable data pipelines on an AWS-based platform while collaborating with data science teams to productionise models. You will support multi-region operations, troubleshoot production issues, and serve as a technical bridge among data science, engineering, and regional teams. The role emphasizes building robust data processing, monitoring, and orchestration to enable data-driven insights at scale. You will contribute to a framework-driven, cross-functional data environment and work across regions to drive impact. Compensation / Benefits * Design and operate large-scale data pipelines on AWS * Productionise machine learning models in collaboration with data scientists * Support multi-region operations and ensure reliability * Troubleshoot production issues across pipelines and models * Monitor data systems and drive continuous operational improvement * Ingest data via batch, file-based, API-based, and streaming methods * Work with data warehousing and analytics stores, optimizing ETL/ELT patterns * Collaborate across regions and time zones with cross-functional teams * Adopt and contribute to the InMedia data science framework * Communicate complex technical issues clearly to stakeholders Tasks * 9+ years hands-on data engineering experience * Deep expertise in AWS-based data platforms (S3, Glue, EMR, Lambda) and Airflow * Strong Python and Spark skills for data processing, orchestration, and production automation * Experience productionising machine learning models (upstream data prep, downstream integration) * Knowledge of data ingestion patterns (batch, file-based, API, streaming) and data warehousing/ETL/ELT * Distributed data processing, data optimization, and scalable ETL/ELT patterns * Experience monitoring, incident resolution, and operational improvement of production data systems * Excellent communication across engineering, data science, and operations * Familiarity with InMedia framework or willingness to adopt * Ability to work effectively across regions and time zones * Nice-to-have: Java/Scala frameworks Key requirements * Flexible working environment * Volunteer time off * LinkedIn Learning * Employee-Assistance-Program (EAP)

• with data warehousing and analytics stores, optimizing ETL/ELT patterns * Collaborate across regions and time zones with cross-functional teams * Adopt and contribute to the InMedia data science framework * Communicate complex technical issues clearly to stakeholders Tasks * 9+ years hands-on data engineering experience * Deep expertise in AWS-based data platforms (S3, Glue, EMR, Lambda) and Airflow * Strong Python and Spark skills for data processing, orchestration, and production automation * Experience productionising machine learning models (upstream data prep, downstream integration) * Knowledge of data ingestion patterns (batch, file-based, API, streaming) and data warehousing/ETL/ELT * Distributed data processing, data optimization, and scalable ETL/ELT patterns * Experience monitoring, incident resolution, and operational improvement of production data systems * Excellent communication across engineering, data science, and operations * Familiarity with InMedia framework or aaa aaaaaax_ to adopt * Ability to work effectively across regions and time zones * Nice-to-have: Java/Scala frameworks Key requirements * Flexible working environment * Volunteer time off * LinkedIn Learning * Employee-Assistance-Program (EAP)