Lead Engineering Manager for Big Data Analytics

hace 1 semana


Madrid, Madrid, España Ravenpack A tiempo completo
About RavenPack

RavenPack is a leading provider of big data analytics solutions for the financial services industry. Our clients rely on us for speed and accuracy in analyzing large amounts of unstructured content.

Our team empowers clients to enhance returns, reduce risk, and increase efficiency by integrating public information into their models and workflows.

The Role

We are seeking an experienced Senior Engineering Manager to lead our engineering projects for the Bigdata Store. This innovative platform provides seamless access to vast collections of structured and unstructured datasets.

You will oversee project planning, execution, and support, ensuring accountability and optimizing operational processes within the dev/ops department.

Your responsibilities include managing cross-functional technical teams, collaborating with Product Management and Project Management, and tracking project milestones and deliverables.

Requirements

To succeed in this role, you must have a strong understanding of engineering principles and practices, as well as proven experience in project management with a track record of successful project delivery.

Key qualifications include:

  • Bachelor's degree in Engineering, Computer Science, or a related field.
  • Minimum 5 years of experience in a coordination or management capacity.
  • Strong organizational and multitasking skills.
  • Effective communication and interpersonal skills.
What We Offer

This is a fantastic opportunity to join a rapidly growing company with 200+ team members across offices in Madrid and New York.

You will work in a collaborative environment where your contribution is valued, and you will have ownership of projects working in an agile environment that can react quickly to changes.

We offer competitive compensation and benefits, including a salary range of $120,000 - $180,000 per annum, depending on experience, plus a bonus structure based on performance.



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