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Job Description
Structured overview of role & requirementsAbout This Role
Design and build scalable, reliable data pipelines using PySpark and big data technologies.
Collaborate with data science to develop features improving model accuracy and performance.
Troubleshoot, optimize ETL workflows, conduct POCs for new technologies, and maintain technical documentation.
Minimum Requirements
5–6+ years of hands-on experience in Data Engineering.
Strong proficiency in Python, advanced SQL, and Apache Spark.
Experience with Apache Airflow, FastAPI, and at least one major cloud platform (AWS, Azure, or GCP).
Foundational understanding of LLMs, AI/GenAI concepts, and familiarity with vector databases, semantic search, knowledge graphs, and preferably RAG architectures.
Ideal Candidate Profile
Experienced in building production-scale data pipelines and integrating AI/ML features collaboratively.
Practically skilled in workflow orchestration, backend development, and cloud infrastructure.
Comfortable evaluating and integrating cutting-edge data and AI technologies into existing platforms.