Gardens Alive

Compensation

Full Description

Description We are seeking a skilled Data Engineer to play a key role in advancing our data-driven culture. The successful candidate will be responsible for creating, supporting, and cascading ETL processes across the enterprise. This position reports to the Head of Analytics and Business Data and will work closely with various business units to ideate and implement unified processes and data analytics capabilities. Requirements Essential Duties and Responsibilities Design and implement data pipelines that seamlessly combine disparate raw data sources - cloud and on-prem - into a modernized Lakehouse Serves as a key liaison between the Analytics department and business leadership to gather and structure business requirements, then create and implement scalable ETL pipelines with suitable semantic layers that collectively create a robust single source of truth for data analysis and BI Visualizations. Works closely with business analytics colleagues to maintain and develop data models and ETL pipelines to power machine learning, data science, and business intelligence workflows Ideates strategies to address data quality concerns and enforce standards. Writes new or modifies existing code and conducts complete end-to-end tests on data and data pipelines As needed, creates APIs to integrate data connections between a modernized Lakehouse and new data sources. As needed, assists with Database Administration tasks Knowledge /Skills/Abilities Bachelor's degree in computer science, Management Information Systems (MIS) or related degree preferred. 2-5 years of hands-on experience implementing, maintaining, and supporting data management solutions including program/project delivery management. Proven experience in technical analysis, critical thinking, troubleshooting and problem-solving skills. Ability to write code using common scripting languages such as SQL, Python, and/or other scripting languages. Experience with ETL tools and techniques and/or pipeline building Proficient with data discovery, data analysis and data virtualization techniques. Full understanding of database concepts, data typing, and database cardinality principles Experience in a data analytics environment working with multiple tables and big-data concepts. Expertise with SQL, SQLServer or MySQL including data troubleshooting, building complex queries, table joins and views working with multiple tables and big-data concepts. Experience with Google Analytics Proficient with process workflow mapping and business process improvement