Data Engineering Lead

il y a 17 heures


Paris, Île-de-France N-iX Temps plein
About the Role

N-iX is a software development service company with a rich history of delivering innovative solutions to Fortune 500 companies and tech startups. Our Data and Analytics practice specializes in data strategy, governance, and platforms, shaping the future for our clients.

Job Summary

We are seeking a forward-thinking and highly skilled Lead Data Engineering professional, specialized in Databricks, to helm the engineering side of a significant data transformation program for our customer. This leader will execute standard data engineering tasks while leveraging advanced techniques like generative AI and automation methods to optimize data and pipeline migrations.

Key Responsibilities
  • Define data architectures, data models, and data integration strategies aligned with business goals.
  • Lead the design and implementation of data pipelines and data lakehouse solutions.
  • Establish scalable data pipelines for analytics use cases.
  • Develop and optimize technical and physical data models.
  • Leverage generative AI to streamline workflows and automate pipeline and data migrations.
  • Collaborate with technology partners to ensure high data quality.
  • Mentor the Data Engineering team for quality code production.
Requirements
  • Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
  • Over 6 years of experience in Data Engineering, with a strong emphasis on architecture.
  • In-depth knowledge of data lakehouse concepts, data management processes, and data integration techniques.
  • Experience with performance tuning and optimization of data pipelines.
  • Innovative mindset with a constant eye on improving the productivity of data engineering work.
What We Offer
  • A competitive salary and good compensation package.
  • Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more).

We offer a flexible working format - remote, office-based or flexible. If you are passionate about data engineering and want to be part of a dynamic team, please apply.


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