Senior Data Engineer (AI)

TL;DR

Senior Data Engineer (AI): Designing, building, and maintaining scalable data infrastructure and pipelines that support machine learning models and large-scale analytics with an accent on data quality, accessibility, and AI solution implementation. Focus on deploying machine learning models and AI tools to production environments, improving data models, and enforcing data governance and security policies.

Location: Hybrid in Greece

Salary: Attractive remuneration package

Company

hirify.global is seeking a skilled Senior Data Engineer to join its Data Science team, driving data-driven decision-making and implementing AI solutions.

What you will do

• Design, develop, and maintain scalable data pipelines for data transformation and preparation.
• Prepare datasets for data analysts and data scientists for exploratory analysis, A/B testing, and model training.
• Ensure data quality and consistency across various sources.
• Deploy machine learning models and AI tools to production environments.
• Collaborate with data scientists to improve data models and support business intelligence tools.
• Build and maintain data warehousing solutions and enforce data governance and security policies.

Requirements

• MSc or PhD in Data Science, Computer Science, Physics, Mathematics, or a related field.
• 4+ years of experience with a focus on data engineering and Python software development (Pandas, NumPy, Scikit-learn).
• Experience with AWS, Google Cloud, or Azure cloud services.
• Extensive experience with relational and non-relational databases.
• Proven experience with machine learning and big data processing and analytics.
• English: C1 required

Culture & Benefits

• Attractive remuneration package and private health insurance.
• Corporate pension fund.
• Intellectually stimulating work environment.
• Continuous personal development and international training opportunities.

Hiring process

• Introductory chat with Talent Acquisition, followed by a first interview with the team.
• Complete a role-specific take-home task.
• Final interview round.