Build and maintain data pipelines and warehousing solutions within an AWS environment.
Responsibilities
- Design and implement ETL processes to move data across cloud environments.
- Manage data warehousing architectures using Snowflake and Amazon Redshift.
- Develop scalable data pipelines using AWS Glue, S3, and Kinesis.
- Apply data modeling techniques to support data science and ML projects.
- Ensure data security and integrity throughout the data lifecycle.
Required Skills
- 6+ years of experience in data engineering roles.
- Expertise with AWS services including AWS Glue, Amazon Redshift, Amazon S3, and Amazon Kinesis.
- Strong programming proficiency in Python, SQL, or Java.
- 2-3 years of hands-on experience with Snowflake and data warehousing concepts.
- Deep understanding of ETL processes and data modeling.
- Solid grasp of cloud computing concepts and data security best practices.
- Experience supporting Data Science and ML project requirements.
- Bachelor's degree or equivalent experience.
Preferred Skills
- Experience with big data technologies such as Apache Spark or Apache Kafka.
- Familiarity with data visualization tools like Tableau or Power BI.
- Understanding of DevOps practices and CI/CD pipelines.