The AI Senior Data Engineer is a key technical driver in our data engineering practice. In this role, you will be responsible for building and optimizing the high-scale ETL/ELT pipelines that power our Generative AI and Machine Learning models. You will focus on the "Data for AI" lifecycle—ensuring that feature engineering, data quality, and model-ready datasets are delivered with high performance and reliability.
Requirements
Technical Mastery: 6–8 years of experience in data engineering with deep proficiency in Python and SQL.
Big Data Stack: Hands-on expertise with Apache Spark/PySpark and the broader Hadoop ecosystem.
Cloud Platforms: Strong experience with at least one major cloud provider (AWS, GCP, or Azure) and their native data tools.
AI/ML Familiarity: Practical experience in feature engineering and preparing datasets for TensorFlow or PyTorch.
Modern Data Stack: Expertise in Snowflake, BigQuery, or Redshift and modern transformation tools like dbt.
DevOps/MLOps: Proficiency with Docker, Kubernetes, and CI/CD for data pipelines.
Compliance & Security: Solid understanding of GDPR basics, data encryption at rest/transit, and access control (RBAC).
Communication: Professional English (C1) for collaboration in global enterprise environments.
Benefits
Remote work model
Professional training programs
Work with a team that is recognized for its excellence. We have been featured in the Deloitte Technology Fast 50 & FT 1000 rankings. We have also received the Great Place To Work® certification for seven years in a row
Questions? Get in touch with the recruitment person hiring for this position!
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* Please Note: different job opportunities may have a slightly different version of this process.
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