Python__Data Engineering
Summary
Build and maintain ETL/ELT pipelines in Python, clean and transform data, and design data warehouses using Snowflake/Redshift/BigQuery.
Job Description
Data Pipeline Development
- Build and maintain ETL/ELT pipelines using Python
- Ingest data from multiple sources (APIs, databases, files, streaming systems)
- Optimize pipelines for performance and scalability
- Clean, transform, and validate raw datasets
Handle structured and unstructured data
Use frameworks like\:
- Pandas
- PySpark
- Dask
Database & Data Warehousing
- SQL (PostgreSQL, MySQL, SQL Server)
- NoSQL (MongoDB, Cassandra)
- Design schemas and optimize queries
- Build data warehouses using\:
- Snowflake
- Redshift
- BigQuery
Big Data Technologies
Apache Spark
Hadoop
Process large-scale datasets efficiently
Workflow Orchestration
Apache Airflow
Cloud Platforms
Work on cloud environments\:
AWS (S3, Glue, Lambda, EMR)
Azure (Data Factory, Synapse)
GCP (Dataflow, BigQuery)
Data Quality & Monitoring
Implement data validation checks
Monitor pipeline failures and fix bugs
- Ensure data reliability and integrity