Data Engineer (Cloud/EDA/Kafka)

Egen is a fast-growing and entrepreneurial company with a data-first mindset. We bring together the best engineering talent working with the most advanced technology platforms, including Google Cloud and Salesforce, to help clients drive action and impact through data and insights. We are committed to being a place where the best people choose to work so they can apply their engineering and technology expertise to envision what is next for how data and platforms can change the world for the better. We are dedicated to learning, thrive on solving tough problems, and continually innovate to achieve fast, effective results.

You will join a team of insatiably curious data engineers, software architects, and product experts who never settle for "good enough". Our Data Engineering teams build scalable data platforms and fault-tolerant pipelines for modern analytics and AI services using Python, SQL, Linux, Bash, and AWS, GCP, or Azure data storage and warehousing services.

As a Data Engineer, you will be the subject matter expert in building event-driven data pipelines, supporting & solving data integration challenges, and cloud-native data warehouse and data lake processing.

Responsibilities:

• Design, document, and develop distributed and event-driven data pipelines with cloud-native data stores such as Snowflake, Redshift, Big Query, or ADW.
• Consult business, product, and data science teams to understand end-user requirements or analytics needs to implement the most appropriate data platform technology and scalable data engineering practices.
• Prepare data mapping, data flow, production support, and pipeline documentation for all projects.
• Delivering completeness of source system data by performing a profiling analysis and triaging issues reported in production systems. 
• Facilitate fast and efficient data migrations through a deep understanding of design, mapping, implementation, management, and support of distributed data pipelines.

What we're looking for:

• Minimum of Bachelor’s Degree or its equivalent in Computer Science, Computer Information Systems, Information Technology and Management, Electrical Engineering or a related field.
• You have a strong background in distributed data warehousing with Snowflake, Redshift, Big Query, and/or Azure Data Warehouse.You have productionized real-time data pipelines through EDA leveraging Kafka or a similar service.
• You know what it takes to build and run resilient data pipelines in production and have experience implementing ETL/ELT to load a multi-terabyte enterprise distributed data warehouse.
• You have a strong understanding and exposure to data mesh principles in building modern data-driven products and platforms
• You have expert programming/scripting knowledge in building and managing ETL pipelines using SQL, Python, and Bash.
• You have implemented analytics applications using multiple database technologies, such as relational, multidimensional (OLAP), key-value, document, or graph.