With a career at The Home Depot, you can be yourself and also be part of something bigger.
Position Purpose:
Online Data Engineer teams at The Home Depot translate business requirements and build the infrastructure needed to capture customer data. They acquire datasets that align with business needs and develop algorithms to transform data into useful, actionable information. Additionally, they build, test, and maintain database pipeline architectures. They create new data validation methods and data analysis tools. Data Engineers develop application programming interfaces (APIs) to retrieve data. Our Data Engineers develop, host, and maintain in-house enterprise solutions to improve reliability and confidence through monitoring, continually testing, and validating the products we support. These associates use big-data techniques to cleanse, organize and transform data and to maintain, defend and update data structures and integrity on an automated basis.
The Sr Data Engineer position creates and establishes design standards and assurance processes for software, systems and applications development to ensure compatibility and operability of data connections, flows and storage requirements. Reviews internal and external business and product requirements for data operations and activity and suggests changes and upgrades to systems and storage to accommodate ongoing needs.
Key Responsibilities:
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Preferred Qualifications:
Demonstrated experience in predictive modeling, data mining and data analysis
2+ years of Search Engine Optimization work experience
Experience in generating content using popular Large Language Models
Demonstrated experience developing and testing ETL jobs/pipelines, configuring orchestration, automated CI/CD, writing automation scripts, and supporting the pipelines in production
Experience in high-level programming languages such as Python
Experience defining and capturing metadata and rules associated with ETL processes
Experience building Batch and Streaming pipelines
Prior direct experience writing analytical SQL queries and performance-tuning queries
Ability to stich and maintain data from multiple sources
Ability to produce tags for site data
Ability to code in Python, Google BigQuery to stitch and enrich the raw data from multiple sources
Proven 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
Ability to prioritize requests and manage a product roadmap
Coaching junior engineers to help improve their code, best practices, and understanding of data engineering principles.
Strong verbal and written communications skills at all levels
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