Senior ML/Data Engineer

Summary

Join Nagarro, a rapidly growing digital product engineering company with a global presence, and contribute your expertise to building cloud-native and hybrid data/machine learning pipelines. Collaborate with a diverse team of engineers and scientists to develop enterprise tools, support research, and optimize data processes. This role requires strong Python skills, experience with various data technologies, and a deep understanding of ML workflows. A degree in Computer Science is required, and a Master's degree is a plus. The ideal candidate will possess experience in a Linux environment and familiarity with data integration/ETL tools.

Requirements

• Degree in Computer Science or similar field; a Master’s is a plus
• Professional experience in software engineering with Python including: Very good understanding of the Python Ecosystem (e.g. NumPy, Pandas, Scikit-learn)
• Coding best practices (e.g. TDD, ATDD)
• Application Architecture and Design Patterns
• Testing strategies
• Versioning
• Significant experience with storage technologies and their advantages and disadvantages (e.g. Relational Database, No-SQL Database, Object Storage)
• Very good understanding of ML Workflows and how to provide suitable infrastructure pieces
• Solid knowledge of HPC and AWS based data engineering and analytics solutions
• Experience with various data integration/ETL tools, application integration, business process and data science tools (e.g. Talend, Kubeflow, Spark, Tableau, Flume, Kafka or Databricks)
• Experience working in a Linux environment

Responsibilities

• Build cloud-native and hybrid data/machine learning pipelines
• Collaborate closely with Solution Architects, Cloud/Backend Architects, Data Security engineers, Data Scientists, and Algorithm Developers
• Actively develop enterprise tools for long-term internal use during ML model research
• Provide technical support for research and early development activities
• Organize and collate raw data
• Prepare data for prescriptive and predictive modeling
• Identify opportunities for automating data processes (e.g. curation, validation)

Preferred Qualifications

• Data engineering certification (e.g AWS Professional Solution Architect, IBM Certified Data Engineer) is a plus
• Experience working in an international environment is a plus