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Job description
You are joining one of the most credible new ventures in quantitative finance before it becomes a household name.
This company is what happens when a global leader in management consulting, part of an NYSE listed professional services firm, joins forces with a highly respected global macro hedge fund. This is not a startup built on a pitch deck. It is a joint venture backed by institutional weight on both the consulting and the buy side, but structured so that early technical hires have real autonomy and real ownership.
You come in on the ground floor. The decisions being made around you carry serious financial consequence, and you are close enough to see and shape them from day one.
Day to day, you are designing and building the data pipelines and platforms that feed advanced analytics and modeling for the firm's clients. You work closely with data scientists, consultants, and clients directly, making sure data is available, reliable, and high quality enough to support real decision-making. This is not a role where engineers sit behind a wall of project managers. You represent the technical function in the room.
You bring 3 to 6 years of experience as a data engineer, with a track record of designing and building data intensive applications and pipelines. You write clean, performant Python and SQL to handle large volumes of data, and you have exposure to some combination of distributed computing tools like Spark or Databricks, cloud platforms such as AWS, Azure, or GCP, orchestration tools like Airflow, and modern engineering practices including version control, CI/CD, and infrastructure as code.
You hold a degree in Computer Science or a quantitative field, ideally from a top ranked university, with a minimum 3.3 or equivalent.
This would be a great next move if you want to skip the slow lane and get close to where financial decisions actually get made.
Ready to build something that matters from the start?
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Worksite address
columbus, OH, 43224, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.