AWS Data Engineer

Primary Responsibilities:
· Implement and manage AWS tools and environment.
· Implement and manage Apache Kafka streams.
· Using Python, build and maintain multiple source data connections to API's, SQL databases, AWS S3, and other sources feeding into a Snowflake Clouds database system.
· Work with internal and external users and providers to build datasets that add value to the business and allow for informed business decisions.
· Ensure data consistency, accuracy and reliability as data and business requirements change.

Required Skills:
· 3+ years of AWS Console, S3, Lambda, Kinesis, Glue, and CloudWatch.
· 3+ years of Kafka streams experience.
· 5+ years of data engineering, data pipeline development, and ETL experience using Python, SQL, and Snowflake
· Experience requesting, transforming, and ingesting data from REST and SOAP APIs
· Proficiency in the Python scripting language, SQL, Cloud databases, and ETL development processes & tools
· Strong understanding of traditional relational databases, data and dimensional modeling principles, and data normalization techniques
· Ability to initiate, drive, and manage projects with competing priorities.
· Ability to communicate effectively with business leaders, IT leadership, and engineers.
· Must have a passion for data and helping the business turn data into information and action.

Bonus Skills:
· Experience with data streaming technologies like PySpark
· Experience with pipeline technologies like DBT, Apache Airflow or FiveTran
· Experience with MPP technologies and databases
· Experience with data visualization tools like Tableau or Sigma
· Experience with container orchestration tools like Docker or Kubernetes
· Experience with Azure data product offerings and platform
· Experience working with Salesforce and SAP data.
· Experience using Terraform or other infrastructure as code tools.
Required Education/Experience:
· Bachelor’s degree in information systems, computer science, or related technical field