The Home Depot's Online Data Engineer teams need to translate business requirements and build the infrastructure to capture customer data, acquire relevant datasets, and develop algorithms to transform data into actionable information. They also need to build, test, and maintain database pipeline architectures, create new data validation methods and data analysis tools, and develop APIs to retrieve data. Additionally, they are responsible for developing, hosting, and maintaining in-house enterprise solutions to improve reliability and confidence through monitoring, testing, and validating supported products, using big-data techniques to cleanse, organize, and transform data, and maintaining data structures and integrity on an automated basis.
Requirements
- Ability to stich and maintain data from multiple sources
- Ability to use JavaScript, Front-end development frameworks (React, Nucleus), and QA apps (Retina, KPI Shield, Alert Goose)
- Ability to produce tags for site data
- Ability to code in Python, Google BigQuery to stitch and enrich the raw data from multiple sources
- Ability to use PySpark, AirFlow, and DataProc to engineer and automate data flows pipelines
- Ability to optimize the pipelines run time and lower the cost on slots/storage consumption
- Demonstrated expertise of how to model and mine data
Responsibilities
- build the infrastructure needed to capture customer data
- acquire datasets that align with business needs
- develop algorithms to transform data into useful, actionable information
- build, test, and maintain database pipeline architectures
- create new data validation methods and data analysis tools
- develop application programming interfaces (APIs) to retrieve data
- develop, host, and maintain in-house enterprise solutions to improve reliability and confidence through monitoring, continually testing, and validating the products we support
Other
- Leverage extensive business knowledge into solution approach
- Effectively develop trust and collaboration with internal customers and cross-functional teams
- Partner with Other Orgs to understand potential for new tools and ways to maintain technical agility for advanced analytics
- Lead and manage large and complex projects and teams
- Provide direction on prioritization of work and ensure quality of work
