Objectives of this position
The objective of the position is to manage the extract / transform / load processes ensuring the data availability.
Responsibilities
- Design, create, modify extract / transform / load (ETL) pipelines in Azure Data Factory ensuring efficient data flow from source to destination.
- Ensure data accuracy and data integrity throughout the ETL processes via data validation, cleansing, deduplication, and error handling to ensure reliable and usable data being ingested.
- Monitor the ETL processes and optimize ETL pipelines for speed and efficiency, addressing bottlenecks, and ensuring the ETL system can handle the volume, velocity, and variety of data.
- Participate in data modeling, designing of the data structures and schema in the data warehouse to optimize query performance and align with business needs.
- Work closely with different departments and IT team to understand data requirements and deliver the data infrastructure that supports business goals.
- Provide technical support for ETL systems, troubleshooting issues and ensuring the continuous availability and reliability of data flows.
- Ensure proper documentation of data sources, ETL processes and data architecture.
Requirements
3 to 5 years of data engineering in Snowflake3 to 5 years in upstream / downstream Retail industry and / or Supply Chain / Manufacturing domainSound Understanding of data quality principles and data governance best practicesProficiency in data analytics languages like Python, Java, Scala, etc.Knowledge of big data technologies like Hadoop, Spark and distributed computing frameworks to manage large scale data processing.Proficient in using version control systems like Git for managing code and configurations.SnowPro Core Certification and SnowPro Advanced Certification will be an advantageJ-18808-Ljbffr