Data Engineer
Skills
DevopsWarehouse OperationsApache SparkData WarehousingDatabasesModelingOracle Application Development Framework
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 15+ years of data engineering experience
- Strong expertise in Python SQL and PySpark
- Experience with AI ML fundamentals and enterprise data engineering
- Hands-on ETL ELT pipeline development
- Apache Spark and Databricks experience
- Data modeling with star and snowflake schemas
- Experience with Airflow Dataflow Informatica ADF Synapse or similar tools
- Knowledge of data lakes and data warehousing
- Experience with REST APIs Git CI CD and DevOps
- Experience with relational and NoSQL databases
- Experience with data preparation for AI ML models
- LLM integration experience with OpenAI Azure OpenAI Gemini Claude or similar
- Experience with RAG pipelines
- Experience with vector databases such as Pinecone ChromaDB or FAISS
- Knowledge of embeddings semantic search and prompt engineering fundamentals
Nice to have
- Retail domain experience
Day to day
- Build and optimize scalable ETL and ELT pipelines for enterprise data modernization
- Develop AI-ready data platforms including data lakes and data warehouses to support ML and generative AI use cases
- Design and implement RAG pipelines LLM integrations and secure data governance practices while collaborating with cross-functional AI teams
Hiring process
- Apply through LinkedIn
- Send updated resume to recruiting team