Senior Data Engineer

● 4+ years of experience handling large data volumes and orchestrating and monitoring automated Batch & Near Real-Time ETL/data pipelines using CI/CD and Cloud Technologies, with preferred expertise in DBT or DBT Cloud.
● Strong programming skills in Python and SQL.
● Solid experience with MPP Data Warehouse systems such as Snowflake or Amazon Redshift, along with cloud platforms including AWS (Preferred), Azure, or GCP.
● Expertise in Data Modelling and Data Warehousing best practices, with a strong ability to adopt development best practices such as modularization, testing, and refactoring.
● Experience with Business Intelligence and reporting tools such as Looker is an added advantage.
● Hands-on experience with Machine Learning (ML) and MLOps practices, including model training, versioning, deployment, monitoring, and lifecycle management using tools like MLflow, SageMaker, or Vertex AI.
● Ability to leverage AI tools in day-to-day data engineering tasks, such as using GitHub Copilot or Claude for code generation, debugging, query optimization, and pipeline development to improve productivity and efficiency.
● Exposure to Generative AI tools and frameworks (e.g., LangGraph, LangChain, OpenAI APIs).
● Curiosity to explore and implement evolving data engineering and Generative AI technologies.
● Understanding of modern practices like DataOps, MLOps or equivalent experience.
● Strong problem-solving skills with a solid understanding of data structures,
algorithms, and the ability to thrive in ambiguous environments with minimal oversight.