GCP Data Engineer

GCP Data Engineer

Location: England (Hybrid)

Salary: £85,000/yr - £95,000/yr

Permanent

GCP Data Engineer – Hadoop/Spark, Kafka, BigQuery, GCP Certified, Python – to £95,000 + 15% Bonus and Benefits – Hybrid

Orbis have partnered with a Google Cloud, Platinum Partner across the UK and Europe . Their focus areas are both application workload migrations and data migrations into platforms engineered on GCP. We are now searching for talented Cloud Data Engineers, to work with fast paced clients, leveraging Cloud as a key driver of their transformation.

You will be a key person in the creation of a new data lake/warehouse/hub built in GCP/Big Data Query and work on the migration of existing ETLs and data to that new platform. Our core toolbox includes Google Cloud Big Data technologies, Scala, Java & Python, Jenkins amongst others.

The ideal candidate for this role will have the following experience:

• Act as a subject matter expert in GCP data technologies.
• Working with stakeholders to determine complex data relationships.
• Supporting the wider Analytics / ML / Assurance Team
• Building and supporting ETL pipelines and processes.
• Verifying the integrity of BI Data by managing and interrogating ETL feeds.
• Work with clients to design and implement modern, scalable solutions using a range of new emerging technologies for the Google Cloud platform.
• Be required to showcase your GCP Data Engineering experience when communicating with clients and their requirements, turning these into technical data solutions.
• Liaise and be part of our extensive GCP community, contributing to the knowledge exchange learning platform.

The ideal candidate for this role will have the following experience and qualifications:

• Hands on and deep experience working with Google Data Products (e.g. BigQuery, Dataflow,
• Dataproc, Vertex AI, Looker, Cloud Data Fusion, Dataprep, etc.).
• Experience in Spark (Scala/Python/Java) and Kafka.
• E2E Data Engineering and Lifecycle (including non-functional requirements and operations)
• management.