Tech Stack
Amazon RedshiftAWSETLMariaDBMongoDBMySQLNoSQLPostgresPythonSQL
About the role
- Discover, analyze and assemble large, complex data sets to meet functional and non-functional business requirements.
- Build ETL pipelines for diverse data sources using SQL and Python in an AWS environment.
- Work with stakeholders (Executive, Product, Engineering) to assist with data-related technical issues and support data needs.
- Develop data tools for business departments to build and optimize products.
- Maintain and optimize existing data models and data architecture.
- Build processes supporting data transformation, metadata, dependencies and workload management.
- Perform root cause analysis on data and processes to answer business questions and identify improvements.
- Predict and validate performance for significant scale increases and manage bottlenecks in advance.
Requirements
- Strong experience with relational SQL and NoSQL databases (Postgres/Redshift, MySQL/MariaDB/Aurora, MongoDB).
- Experience with Python.
- Experience with AWS services: S3, Athena, Redshift, Glue.
- Experience building, optimizing and supporting big data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes.
- Experience building processes for data transformation, data structures, metadata, dependency and workload management.
- Ability to predict and validate performance at 10x, 100x, 1000x scale and manage bottlenecks.
- Experience supporting and working with cross-functional teams (Executive, Product, Engineering) in a dynamic environment.