Partner with data scientists and business stakeholders to understand data needs and help build data products that scale across the company
Drive the collection of new data from first-party and third party data sources via APIs and the refinement of existing data sources.
Enhance Cowbell Connector platform in terms of adding new functionality, usability and observability.
Implement tools for monitoring and ensuring data quality and consistency
Collaborate with Architects and Lead Engineers to implement and maintain the standards and consistency for the data-pipelines and best practices
Experience in Continuous Integration, Delivery, and Deployment software tools to support, enhance, and grow our CI and CD capabilities
Experience in containerization using Docker and Kubernetes.
Develop and maintain effective working relationship with data suppliers

What Cowbell needs from you:

Solid experience in data ingestion and integration by consuming third-party APIs.
Proficient in one or more programming languages such as Java, Python etc. and rock-solid SQL skills
Experience implementing a data lake architecture and/or enterprise data solutions.
Experience with Data Warehousing solutions such as Snowflake, Redshift or similar solutions

Preferred qualifications:

7+ years of experience in Data Engineering, 4 of which specific use of Python
Bachelor's or Master’s Degree in Computer Science, Information Systems, or other related field
Experience building large scale distributed data systems
Experience working with AWS/GCP/Azure big data technologies
Experience with distributed computing technologies like Apache Kafka, Spark etc.
Knowledge in data modeling, ETL development, and data warehousing
Knowledge of database and software engineering best practices across the development lifecycle including
Strong communication skills and experienced in gathering requirement

This is a hybrid role, which will require 3 days in office.

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