Key skills
AirflowAmazon RedshiftAWSBigQueryDockerEC2ETLMongoDBMySQLNoSQLOraclePostgresPythonRDBMSSQLMachine LearningData EngineeringAnalyticsBusiness IntelligenceSnowflakeRedshiftdbtECSS3AthenaSQL ServerGitSaaS
About this role
Role Overview
- Build and deploy the data pipelines that power Companys machine learning platform.
- Develop warehouse architectures that integrate data from diverse sources.
- Design analytics solutions for both product development and internal collaborators.
Requirements
- A minimum of 1 years experience in data engineering, analytics engineering, or software engineering with an emphasis on large scale data management and processing systems.
- Proficiency in Python and advanced SQL.
- Advanced experience with ETL pipelines, data modeling and managing data warehouses (Snowflake, BigQuery, Redshift, etc).
- Experience with SQL RDBMS such as MySQL, Postgres, Oracle, SQL Server, etc., as well as NoSQL systems such as MongoDB is required.
- Experience with tools including Meltano, dbt, Airflow, and Superset is required.
- Experience with Docker, Git and AWS (EC2, ECS, S3, Step Functions, and Athena).
- Analytics and Business Intelligence knowledge is highly preferred.
- Experience working with common SaaS APIs (such as CRMs) is preferred.
Tech Stack
- Airflow
- Amazon Redshift
- AWS
- BigQuery
- Docker
- EC2
- ETL
- MongoDB
- MySQL
- NoSQL
- Oracle
- Postgres
- Python
- RDBMS
- SQL