About the role
Infinitive is hiring a Technical Recruiter to find and hire the data and AI talent our client’s work depends on. You will run several searches at once for Data Engineers, Data Architects, and AI Engineers, many of them with hands-on Databricks experience. You will also source consultants with strong functional and foundational consulting experience in program management, change management, AI Adoption, and training.
Priorities here change as client demand changes. A new engagement can open three roles on Monday, and a client decision can put one on hold by Wednesday. You will adjust your plan quickly, keep every search moving, and keep hiring managers informed about where each one stands.
What you will do
Run full-cycle recruiting for several open searches at a time, each with its own candidate persona (for example, a senior Databricks Data Architect, a mid-level Data Engineer, and an AI Engineer building RAG applications).
Hold intake meetings with hiring managers and practice leads. Ask follow-up questions until the must-have skills, seniority, certifications, clearance needs, client context, and compensation range are clear before sourcing starts.
Source passive and active candidates through LinkedIn Recruiter, GitHub, Databricks community channels, job boards, referrals, and your own network.
Screen candidates on technical fit, including Databricks (Delta Lake, Unity Catalog, Spark, Databricks SQL), cloud platforms (AWS, Azure), Python and SQL, data modeling, and AI/ML tooling.
Re-rank your searches when priorities change and tell hiring managers what moved and what it means for their timelines.
Manage the candidate experience from first contact through offer, including scheduling, feedback, offer conversations, and closing.
Keep the applicant tracking system current so anyone can see the status of every search and candidate.
Build and maintain a bench of data and AI candidates for roles Infinitive expects to open.
What you bring
2+ years of technical recruiting experience, with a track record of filling data engineering, data architecture, or AI/ML roles.
Experience sourcing and hiring Data Engineers, Data Architects, and AI Engineers, including candidates with Databricks experience.
Enough technical knowledge to hold a credible first conversation about Spark, lakehouse architecture, cloud data platforms, and machine learning, and to tell a strong Databricks profile from a keyword match.
Experience managing multiple searches at once without letting any of them stall.
Strong written and verbal communication with candidates, hiring managers, and executives.
Strong organizational habits: clean ATS records, tracked follow-ups, and searches anyone could pick up from your notes.
Comfort with ambiguity. When a request is unclear, you ask questions until it is clear rather than guessing.
Nice to have
Experience at a technology staffing firm or IT services consultancy, where you recruited against client deadlines and changing requirements.
An existing network of Databricks, data engineering, or AI practitioners.
Familiarity with Databricks certifications (Data Engineer Associate and Professional, and Machine Learning Associate) and what each one says about a candidate.
Experience recruiting candidates with security clearances for public sector work.
Experience with Boolean and X-ray search techniques and recruiting automation tools.
How you work
You move fast and stay organized when the plan changes. A reprioritized search does not mean a dropped one.
You switch focus quickly between searches, candidates, and hiring managers without losing track of where each one stands.
You act before you are asked. You spot a stalled search, a slow interview loop, or a candidate about to accept another offer, and you raise it.
You ask probing questions. You find out why a role is open, what the client needs, and what "senior" means for this team before you send a single profile.
You communicate clearly and often, so hiring managers and candidates know what is happening and what comes next.
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