Responsibilities:

• Lead and develop passionate data engineering teams to design and develop distributed and event-driven data pipelines with cloud-native data stores such as Snowflake, Redshift, Big Query, or ADW.
• Design, document, and lead development of end-to-end data product pipelines
• 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.
• Lead data engineering and/or operations teams in 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 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 data warehouse.
• You have a strong understanding and exposure to data mesh principles in building modern data-driven products and platforms
• You have a strong background in distributed data warehousing with Snowflake, Redshift, Big Query, and/or Azure Data Warehouse.
• 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.