Develop and support ETL pipelines with robust monitoring and alarming
Develop data models that are optimized for business understand-ability and usability
Develop and optimize data tables using best practices for partitioning, compression, parallelization, etc.
Develop and maintain metadata, data catalog, and documentation for internal business customers
Help internal business customers troubleshoot and optimize SQL and ETL solutions to solve reporting problems
Work with internal business customers and partner technical teams to gather and document requirements for data publishing and consumption
Develop and collaborate with engineers on Machine Learning initiatives.
Bachelors degree in Computer Science, Engineering, Mathematics, or a related technical discipline
8+ Years of industry experience in Data Engineering, BI Engineer or related field with experience manipulating, processing, and extracting value from large datasets
Ability to write high quality, maintainable, and robust code, often in SQL, Scala and Python.
5+ Years of Data Warehouse Experience
Demonstrated strength in SQL, scripting, data modeling, ETL development, and data warehousing
Extensive experience working with cloud services (preferably GCP) with a strong understanding of cloud databases (e.g. BigQuery/Firestore), compute engines, data streaming , storage
Experience/Exposure using big data technologies
Experience in Machine Learning
Masters in computer science, mathematics, statistics, economics, or other quantitative fields
5+ years of direct experience as a Data Engineer
Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
Proven success in communicating with users, other technical teams, and senior management to collect