Senior Data Engineer, Ruggable

• Minimum of 3+ years relevant experience as a Data Engineer
• Proficiency in scripting languages like Python or Bash
• Familiarity with version control systems such as Git
• Working knowledge of API integration or Stream-based data extraction and structured, semi-structured and unstructured file formats
• Design, develop and own robust, scalable data processing and data integration pipelines using Python, DBT, Kafka, Airflow, and Spark to ingest data from a variety of external data sources to a data lake
• Deep understanding of SQL with relational data stores and column-oriented database systems such as Redshift, Postgres, and CockroachDB
• Ability to interact cross-functionally with non-technical departments
• Ability to work individually or as part of a team
• Support and expand standards, guidelines, tooling, and best practices for data engineering
• Local to Los Angeles, Chicago, or Charlotte

Desirable

• Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
• You will be responsible for developing and optimizing big data pipelines, architectures, and data sets.
• In-depth knowledge of Modeling and Design of DB schemas for read-and-write performance.
• Promoting Data Engineering best practices within the team and mentorship opportunities.
• Develop highly scalable data pipelines to load data from various source systems, and use Apache Airflow to orchestrate, schedule and monitor the workflows.
• As a Senior Data Engineer at Ruggable, you will own, contribute, and extend the business’s data pipelines by extracting, storing, processing, and transforming large data sets
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management. You will be responsible for developing and optimizing big data pipelines, architectures, and data sets. In-depth knowledge of Modeling and Design of DB schemas for read-and-write performance. Promoting Data Engineering best practices within the team and mentorship opportunities. Develop highly scalable data pipelines to load data from various source systems, and use Apache Airflow to orchestrate, schedule and monitor the workflows