Data Engineer for Verity, a digital transformation consultancy, designing data architectures and building scalable pipelines. Collaborates on data quality and analytical dataset structuring.
Responsibilities
Will work on designing and evolving data architectures, building scalable pipelines, and implementing engineering best practices in cloud environments.
Will play a key role in evolving the data architecture and defining technical standards.
Design and evolve scalable data architectures in cloud environments.
Develop robust pipelines for data ingestion, transformation, and delivery.
Define data engineering and data quality best practices.
Structure analytical datasets to support analytics and machine learning initiatives.
Optimize performance and governance of data environments.
Support analytics teams in structuring datasets and pipelines.
Contribute to continuous improvements in architecture and engineering processes.
Requirements
Proven experience in data engineering.
Experience with Python and advanced SQL.
Experience with BigQuery or modern data warehouses.
Experience with cloud environments (preferably GCP).
Experience building pipelines and modeling analytical data.
Experience with layered data architectures (Medallion / Lakehouse).
Nice-to-haves / Differentials:
Experience with Vertex AI or advanced data platforms.
Experience with DataOps / MLOps.
Experience with large-scale analytical environments.
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