Requirements

• Experience with data modeling, warehousing and building ETL pipelines
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• Experience with SQL
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• Experience as a Data Engineer or in a similar role
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• Experience building large-scale, high-throughput, 24x7 data systems
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• (Desirable) Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
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• (Desirable) Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
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• (Desirable) Experience with software development lifecycle, or experience operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets

What the job involves

• This role will sit within a data and analytics team supporting two large program teams (EU AVS and VX) while working closely with BIEs, scientists and 15+ Product Managers
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• As a Data Engineer, you will design, develop, and maintain highly scalable data pipelines and storage solutions to support advanced analytics, machine learning (ML), and artificial intelligence (AI) initiatives. You will be instrumental in ensuring the availability, reliability, and scalability of data systems that drive insights and actions for the team
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• Data Architecture & Pipelines: Design and implement data pipelines and ETL processes to ingest, process, and manage structured and unstructured vendor feedback data at scale
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• Collaborative Development: Partner with BIEs and scientists to provide clean, production-ready datasets
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• Scalable Solutions: Build and optimise data infrastructure to support the processing of structured and unstructured vendor data
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• Insights & Reporting: Create robust systems for monitoring and reporting on key metrics, enabling cross-functional teams
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• Automation: Automate processes for data collection, validation, and transformation to improve efficiency and accuracy across global vendor touchpoints