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Job Description
Structured overview of role & requirementsAbout This Role
Develop and maintain scalable ETL/ELT data pipelines and data transformation solutions using Python, PySpark, SQL, and cloud platforms like Databricks and Azure.
Support migration of datasets and pipelines to modern cloud-based data platforms with data validation and quality checks.
Collaborate with cross-functional teams to prepare and process structured and unstructured datasets for AI-enabled use cases including Generative AI and LLMs.
Minimum Requirements
2 to 5 years of experience in Data Engineering, Data Analytics Engineering, or related role.
Bachelor's degree in Computer Science, Information Technology, Engineering, or related field.
Hands-on experience with Python, SQL, Spark/PySpark, Databricks or similar cloud platforms, and Azure cloud services.
Work Experience Required: 2-5 years relevant Data Engineering experience.
Ideal Candidate Profile
Experienced in building and supporting cloud-based ETL/ELT pipelines with strong data engineering fundamentals.
Comfortable working with both structured and semi-structured data and migrating legacy datasets to cloud platforms.
Interested in and willing to learn emerging AI technologies including Generative AI, LLMs, embeddings, and AI-assisted data engineering automation.