Data Engineer

Key JD requirements: Design, develop and maintain data integration pipelines/interfaces between Crew. Connect and upstream/downstream systems. Analyse existing data flows, mappings and dependencies and support interface enhancements. Build and support reliable data ingestion, transformation and validation, ensuring data quality and integrity.

Troubleshoot data/interface issues and perform root-cause analysis with application/product teams. Translate crew/resource scheduling data requirements into scalable integration and data-engineering solutions. Technical Environment: The role works across Snowflake, DBT, AWS cloud services, Git-based DevOps pipelines, enterprise integrations, and reporting ecosystems supporting Crew.

Connect and broader People Domain initiatives. Data solutions are deployed within cloud-native environments leveraging modern engineering practices, automation, and governance frameworks to support scalable enterprise data products. Essential Capabilities and Experience Advanced experience in SQL development and data modelling for enterprise-scale solutions.

Strong experience designing and implementing data solutions using Snowflake. Proven experience with DBT for data transformation, testing, documentation, and deployment. Experience implementing and supporting Git-based DevOps practices and CI/CD pipelines. Strong understanding of data governance principles, including data quality, metadata, lineage, stewardship, and access controls.

Exposure to AWS services such as S3 and IAM. Experience designing scalable data pipelines and ETL/ELT processes. Ability to analyse complex business requirements and translate them into maintainable data solutions. Strong problem-solving skills with the ability to investigate and resolve data quality, performance, and integration issues.

Effective communication and collaboration skills across business and technical teams. A qualification in Computer Science, Engineering, Information Systems, Data Analytics, or equivalent practical experience.