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About the role
8+ years of experience as a Data Engineer with 2+ years focused on MLOps.
Excellent English communication skills.
Effective oral and written communication skills with BI team and user community.
Demonstrated experience in utilizing python for data engineering tasks, including transformation, advanced data manipulation, and large-scale data processing.
Deep understanding of vector databases and RAG architectures, and how they drive semantic retrieval workflows.
Skilled at integrating open-source LLM frameworks into data engineering workflows for end-to-end model training, customization, and scalable inference.
Experience with cloud platforms like AWS or Azure Machine Learning for managed LLM deployments.
Hands-on experience with big data technologies including Apache Spark, Hadoop, and Kafka for distributed processing and real-time data ingestion.
Experience designing complex data pipelines extracting data from RDBMS, JSON, API and Flat file sources.
Demonstrated skills in SQL and PLSQL programming, with advanced mastery in Business Intelligence and data warehouse methodologies, along with hands-on experience in one or more relational database systems and cloud-based database services such as Snowflake/Redshift.
Understanding of software engineering principles and skills working on Unix/Linux/Windows Operating systems, and experience with Agile methodologies.
Proficiency in version control systems, with experience in managing code repositories, branching, merging, and collaborating within a distributed development environment.
Interest in business operations and comprehensive understanding of how robust BI systems drive corporate profitability by enabling data-driven decision-making and strategic insights.
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