Data Engineering Manager

40 000 - 50 000 PLN/ mies.Umowa o pracę (brutto)
SeniorFull-time·Umowa o pracę
#357480·Dodano wczoraj·0
Źródło: nofluffjobs.com
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Tech Stack / Keywords

Data engineeringSystem architectureDistributed systemsScalable data platformsPythonSQLData baseData pipelinesAPIWeb technologiesCloud-based environmentsCommunication skillsStakeholder managementPeople leadership skills

Firma i stanowisko

We are seeking a senior engineering leader to join a high-impact data acquisition team focused on delivering unique datasets that support investment research and decision-making. This role combines people management, technical leadership, and AI-driven automation to help transform large volumes of structured and unstructured data into actionable insights.


Wymagania

  • 7–8+ years of software or data engineering experience, including experience leading engineering teams.
  • Strong background in system architecture, distributed systems, and scalable data platforms.
  • Proficiency in Python and SQL/databases.
  • Experience with data pipelines, APIs, web technologies, and cloud-based environments.
  • Ability to operate both strategically and hands-on at a technical leadership level.
  • Strong communication, stakeholder management, and people leadership skills.

Obowiązki

  • Lead, mentor, and develop a team of data engineers, driving technical excellence and delivery.
  • Own high-level architecture, system design, technical strategy, and engineering best practices.
  • Review technical solutions and provide guidance on scalability, reliability, and performance.
  • Design scalable systems for collecting, processing, and standardizing alternative data from web, audio, video, and other sources.
  • Drive automation and AI-enabled solutions to improve data extraction, validation, and operational efficiency.
  • Partner with technology, data, and research teams to deliver robust infrastructure and solutions aligned with business needs.
  • Collaborate with distributed teams and external resources to scale data operations and quality processes.
  • Stay current with emerging technologies and identify opportunities for innovation.
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