Key skills
PythonSQLETL pipelinesData modelingData warehousesSnowflakeBigQueryRedshiftMySQLPostgresOracleSQL ServerMongoDBMeltanodbtAirflowSupersetDockerGitAWS EC2AWS ECSAWS S3AWS Step FunctionsAWS AthenaBusiness IntelligenceSaaS APIsNoSQLMachine LearningETLData EngineeringAnalyticsAWSECSEC2S3AthenaSaaS
About this role
PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. They are looking for a savvy Data Engineer to join their growing team, responsible for expanding and optimizing data pipeline architecture and data flow for cross-functional teams.
Responsibilities:
- Build and deploy the data pipelines that power PatternAI’s 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 4 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