Our client approached Recruitment Legends after spending approximately two months attempting to fill a highly specialised Data Engineer position through internal efforts and other recruitment channels. The role required a rare combination of niche technical expertise, specifically hands-on experience with Kafka and Iceberg. But the challenge extended beyond technical capability alone.
Our client was deliberately avoiding candidates with purely banking-sector backgrounds. While professionals with these skills are heavily concentrated in financial services environments, our client needed someone with broader industry exposure and a different perspective to contribute to their engineering team. This significantly narrowed the available talent pool and made sourcing considerably more complex.
In a South African market where skilled Data Engineers are already in short supply, finding candidates with both the required technical stack and the right industry background demanded a targeted headhunting strategy rather than conventional recruitment methods.
Rather than relying on active applicants, we conducted a focused headhunting campaign to identify passive talent already employed within aligned industries. We began with a deep consultation with our client’s team to fully understand why non-banking industry exposure was critical to the success of the hire, not just what the job specification required.
Over the course of the search, approximately 10 candidates were screened and interviewed. The successful candidate was proactively approached while employed in another role.
Within approximately five weeks of commencing the search, the role was successfully filled with a candidate who matched both the technical requirements and the broader industry exposure our client had prioritised. The placement resolved a hiring challenge that had remained open for over two months before Recruitment Legends was engaged.
The success of the placement was built on:
