Sr Data Engineer - Assortment and Space Planning

The Home Depot; Atlanta (GA); On-site; USD 120,000 - 170,000; Full time

Job summary

The Home Depot is seeking a Data Engineer to join the Assortment and Space Planning Data Science team in Atlanta. You will translate business needs into scalable data pipelines, cleanse and organize data, and develop data products to improve analytics reliability and confidence.

Ideal candidates will have 5+ years in data engineering, strong SQL/Python, experience with data warehousing, dbt or Dataform, and ability to collaborate across teams to deliver high-quality data solutions.

Qualifications

• Bachelor's degree in a quantitative/technical field and 5+ years of experience.
• Experience in data architecture, warehousing, and dimensional modeling.
• Proficient in ETL/ELT development, orchestration, and CI/CD tooling.
• Experience with data transformation tools like dbt or Dataform.
• Strong Python and SQL skills; able to write and tune analytical queries.
• Ability to stitch data from multiple sources and optimize pipelines.

Responsibilities

• 40% - Validate data, build ETL/infrastructure for reliable data integration.
• 30% - Maintain data infrastructure, back up, optimize, ensure data integrity.
• 20% - Design/analyse data architectures to meet business needs.
• 10% - Collaborate with leads and partners to assess requirements.

Skills

ETL pipelines

Data validation

Data architecture

SQL

Python

BigQuery

CI/CD

Data warehousing

Data quality tooling

Streaming data

Education

Bachelor's degree in Computer Science/Engineering

Master's degree (preferred)

Tools

dbt

Airflow

Google Cloud / BigQuery

Job description

With a career at The Home Depot, you can be yourself and also be part of something bigger.

Position Purpose:

Data Engineers within the Assortment and Space Planning Data Science team translate business requirements and build the infrastructure needed to structure and deliver the data that powers self-service analytics and hardened business applications. They acquire datasets that align with business needs and develop pipelines to transform data into useful, actionable information. Additionally, they build, test, and maintain data pipeline architectures, create data validation methods and data quality tooling, and develop, host, and maintain data products to improve reliability and confidence through monitoring, testing, and validation. These associates use modern data engineering techniques to cleanse, organize, and transform data, and to maintain, defend, and update data structures and integrity on an automated basis.

Key Responsibilities:

• 40% Data Validation, ETL, Infrastructure Development: Coding validation and ETL to ensure successful data integration
• 30% Data Infrastructure Maintenance: Backup and optimization activities to maintain performance; code, configure, test, etc data to ensure integrity
• 20% Data Architecture Design and Analysis: Create and maintain optimal data pipeline architecture; Develop data architecture to meet business requirements
• 10% Planning/Requirements Analysis: Collaborate with team leads and cross functional partners to assess business requirements and communicate opportunities

Direct Manager/Direct Reports:

• This position reports to the Technology Leader.
• This position has 0 direct reports.

Travel Requirements:

• Typically requires overnight travel less than 10% of the time.

Physical Requirements:

• Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Working Conditions:

• Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications:

• Must be eighteen years of age or older.
• Must be legally permitted to work in the United States.

Preferred Qualifications:

• Bachelor’s or Master’s in a quantitative or technical field (Computer Science, Engineering, Statistics, etc.) or relevant work experience
• 6+ years of relevant work experience
• Demonstrated experience in data architecture, data warehousing, and dimensional modeling
• Demonstrated experience developing and testing ETL/ELT jobs and pipelines, configuring orchestration, automated CI/CD, writing automation scripts, and supporting pipelines in production
• Experience with Dataform or dbt for data transformation and pipeline orchestration
• 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 (preferably Google BigQuery)
• Ability to stitch and maintain data from multiple sources
• Ability to optimize pipeline runtime and lower cost on slot/storage consumption
• Ability to prioritize requests and manage a pipeline roadmap
• Coaching junior engineers to help improve their code, best practices, and understanding of data engineering principles
• Strong verbal and written communication skills at all levels

Minimum Education:

• The knowledge, skills and abilities typically acquired through the completion of a bachelor’s degree program or equivalent degree in a field of study related to the job.

Preferred Education:

• No additional education

Minimum Years of Work Experience:

• 5

Preferred Years of Work Experience:

• No additional years of experience

Minimum Leadership Experience:

• None

Preferred Leadership Experience:

• None

Certifications:

• None

Competencies:

• Collaborates - Building partnerships and working collaboratively with others to meet shared objectives
• Communicates Effectively - Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences
• Cultivates Innovation - Creating new and better ways for the organization to be successful
• Drives Engagement - Creating a climate where people are motivated to do their best to help the organization achieve its objectives
• Instills Trust - Gaining the confidence and trust of others through honesty, integrity, and authenticity
• Nimble Learning - Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder
• Optimizes Work Processes - Knowing the most effective and efficient processes to get things done with a focus on continuous improvement
• Plans and Aligns - Planning and prioritizing work to meet commitments aligned with organizational goals
• Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.