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Lead Data Engineer

ZipRecruiter

Rostock

Vor Ort

EUR 90.000 - 100.000

Vollzeit

Vor 3 Tagen
Sei unter den ersten Bewerbenden

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Zusammenfassung

A leading company in digital technology seeks a Lead Data Engineer in Rostock. The role involves leading Data & AI projects, conducting technical evaluations, and fostering a culture of learning. Ideal candidates have 5+ years' experience, strong skills in data architecture, and are fluent in English and German.

Qualifikationen

  • 5+ years of professional experience in data architecture or engineering with leadership experience.
  • Strong affinity for mathematics and statistics.
  • Fluent in English and German; knowledge of the energy industry is a plus.

Aufgaben

  • Act as primary liaison for the leadership team and mentor team members.
  • Lead Data & AI projects with internal clients, ensure quality through agile processes.
  • Conduct technical evaluations of new candidates during hiring.

Kenntnisse

Data Architecture
Leadership
Azure
AWS
GCP
Machine Learning
Python
SQL
ETL Processes
Infrastructure-as-Code

Ausbildung

Degree/PhD in Computer Science or related discipline

Tools

Azure Data Factory
Azure Databricks
Azure Synapse Analytics
Terraform
ARM templates

Jobbeschreibung

Job Description

Position - Lead Data Engineer

Salary - 90k-100k

Given the significant responsibilities we bear towards our customers, assets, and the environment, we're dedicated to analyzing and developing innovative solutions. Leveraging advanced big data and machine learning technologies, our aim is to deliver optimal services, enhance efficiency, and promote smarter, cleaner practices.

Your Responsibilities:

  • Act as the primary liaison for the leadership team, fostering mentorship among team members and cultivating a culture of continuous learning.
  • Provide support for projects and initiatives, particularly in their initial setup phase. Collaborate with the team to devise suitable architectures, estimate efforts, and assign appropriate Data Engineers.
  • Lead Data & AI projects closely with internal clients, ensuring high quality and stability through agile processes and peer code reviews. Enhance efficiency and time-to-market by implementing reusable data models, architecture templates, and deployable data products.
  • Take charge of technical evaluations of new candidates during the hiring process.
  • Stay updated with industry trends and emerging technologies in data architecture and engineering. Evaluate and recommend new tools, technologies, and methodologies to enhance data management and analysis capabilities.

Your Skills:

  • Possess 5+ years of professional experience in data architecture or engineering, with leadership experience and a degree/PhD in Computer Science or a related technical discipline. Strong affinity for mathematics and statistics.
  • Extensive knowledge of Azure, AWS, and GCP cloud environments, along with architecture best practices and tools relevant for machine learning/AI use cases. Hands-on experience with Infrastructure-as-Code frameworks like Terraform and/or ARM templates.
  • Proven experience in ETL processes, data extraction, transformation, and loading with Azure Data Factory, Azure Databricks, and/or Azure Synapse Analytics. Familiarity with DevOps, CI/CD pipelines, and deployment best practices.
  • Proficient in Machine Learning frameworks like sci-kit-learn, Tensor Flow, PyTorch, Azure ML, etc. (including ML interpretability). Excellent programming skills in Python & SQL.
  • Strong communication and presentation skills, adaptable to varying levels of precision and audience, fluent in English and German. Knowledge of the energy industry is advantageous.

What to Expect from a Career in Digital Technology:

Embark on a unique journey that combines your passion for technology with the opportunity to work on topics of high societal relevance. Contribute to our ambitious digitalization strategies, broaden your expertise through diverse assignments, work with cutting-edge technology, and explore international career growth opportunities within the organization.

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