Description

Key Responsibilities

Develop and optimize cloud-based data storage and processing solutions using Snowflake.
Design, implement, and maintain robust data pipelines and ETL processes
Collaborate with Federated teams and other data engineers to understand data requirements and deliver high-quality data solutions.
Ensure data integrity and security across all data workflows and storage solutions.
Monitor and troubleshoot data pipelines, addressing any issues promptly to ensure the smooth flow of data.
Develop reusable and modular stored procedures and scripts for data processing.
Contribute to the development and implementation of data governance and best practices.
Monitor and troubleshoot data pipelines to ensure reliability and accuracy.
Implement best practices for data governance, data quality, and metadata management.



Minimum Qualifications

Bachelor’s or master’s degree in computer science, Engineering, or a related field.
Minimum of 12 years of experience in data engineering or a related role.
Proven experience with Snowflake is required.
Knowledge of data warehousing concepts, dimensional modeling, and performance tuning.
Hands-on experience with ETL tools (e.g., Informatica, Talend, dbt, or custom ETL frameworks).
Strong proficiency in SQL and database management.
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Familiarity with version control (Git) and CI/CD for data pipelines.
Familiarity with Big Data technologies such as Hadoop, Spark, and Kafka is a plus.
Excellent problem-solving and analytical skills.
Strong communication and collaboration abilities.

Experience with Python or other scripting languages.
Experience with informatica but not necessary.
Knowledge of data visualization tools such as Tableau or Power BI.
Exposure to data orchestration tools
 

Key Skills

Education

Bachelor's or Master's degrees