Building Data Teams #3: Data Engineer
Building Data Teams: a case study series sharing how DR Analytics Recruitment works with businesses and data professionals.
Introduction: Setting the Scene
One brisk Tuesday morning, outside of the usual LinkedIn chaos that is a recruiter's inbox, there was a different message. It was an individual who I'd reached out to regarding a role - but they weren't looking for a change - they were looking to help finding a Data Engineer.
Me: "Hello, Douglas speaking."
New Client: "Hey Douglas, we've seen your LinkedIn content and appreciate your specialisation in data & analytics - you might be just what we need."
Me: "That's what we do. How can I help?"
New Client: "We've got a difficult one: contract Data Engineer with multiple agencies competing."
Me: "Don't tempt me with a challenge!"
The Stack
The client's environment was an enterprise data platform (EDP) based on Azure Databricks, orchestrated with Azure Data Factory and managed through Azure DevOps. They were looking for an experienced data engineer to enhance their in-house capabilities and instill best practices in both Azure Data Factory and Databricks. Key responsibilities included:
Expertise in Databricks, specifically features like unity catalog, delta live, and autoloader
Proven experience developing governance protocols for monitoring and addressing errors
Skills transfer and in-house development
Databricks & Azure Architecture
The Search
This was a specialised role so we needed scalpel-like outreach. Posting on LinkedIn and traditional job portals might not yield quick results. My approach was more targeted:
Internal Database: I combed through our extensive internal database, filtering for data engineers with specific skills in Azure Databricks and Data Factory.
LinkedIn Recruiter: This proved to be a valuable resource, especially for passive candidates who were open to new opportunities.
LinkedIn Job Advertisement: Different from Seek, LinkedIn pushes the job ad to the individual who is best suited. Sort of like targeted advertising. This relies on top ad content and quality to be successful.
After a week of sourcing and interviewing, we had narrowed it down to one viable candidates. They went through the behavioural and technical interviews with client and came out successful.
Contract Issued, and Action!
The contract was quickly executed, and the candidate began the onboarding process. We will be closely monitoring the initial weeks to address any gaps and provided continuous support.
Outcome
The recruitment engagement was successful with both client and candidate parties happy. One critical lesson learned was the importance of multiple sourcing avenues. Relying purely upon a job advertisement is a sure way to fail. At minimum, there should be at least three ways that an individual can find out and express interest in a job.
Conclusion: The Value of the Journey
At DR Analytics Recruitment, we go beyond just recruiting; we become a part of your extended data team, ensuring that we understand both the technical and business aspects of your requirements. Our expertise in the data engineering space enables us to find not just a candidate but the right candidate. We're here to build future-ready data teams.
For inquiries:
📧 Email: douglas@analyticsrecruitment.com.au
📞 Phone: +61 430 846 876
🌐 Website: https://www.analyticsrecruitment.com.au
Feel free to reach out if you're looking to build a strong data engineering team or want to be a part of one!
