Once the data environment was configured, the 3 Engineers shared responsibility for CI/CD and deployment, gaining valuable MLOps skills that they had not used in production before.

They needed to build the team. We worked with them to truly understand their style of working and management. This resulted in the team’s first 2 hires, followed by another 5 hires across data engineering and machine learning over an 18-month period.

We provided salary bandings plus information about motivations for moving and skills that are in demand, leading to the placement of 3 Cloud Data Engineers including a lead after approving salaries and agency budget.

The Head of Data Engineering needed this team built fast, so we agreed to keep open lines of communication and for 24-hour CV turnaround and suggested streamlining the process as much as possible due to the nature of such a competitive talent market.

Scala and Kafka were initial sticking points for the manager, so we pressed for suitable alternatives to increase the flexibility. They agreed to consider candidates with different streaming experience and programming backgrounds which opened a larger pool. We placed 3 highly technical hires.