Logo for The Home Depot

Online Sr Data Engineer - Remote

Role overview

Qualifications

  • Bachelors or Masters in a quantitative field or relevant work experience
  • 5+ years of relevant work experience
  • Demonstrated experience in predictive modeling, data mining and data analysis
  • Strong verbal and written communications skills at all levels

Responsibilities

  • Leverage extensive business knowledge into solution approach and collaborate with internal customers
  • Work with project teams to determine project goals and provide mentorship to junior roles
  • Execute tasks with efficiency and communicate insights and recommendations to stakeholders
  • Guide project teams in the requirements gathering, design, and development of complex applications

Key facts

Hard skills

Other skills

  • Communication
  • Collaboration
  • Coaching

About the company

The Home Depot logo

The Home Depot

Retail – Home Improvement & Building Supplies

The Home Depot, the world’s largest home improvement specialty retailer, values and rewards dedicated, knowledgeable, and experienced professionals. We operate more than 2,300 retail stores in all 50 states, the District of Columbia, Puerto Rico, the U.S. Virgin Islands, Guam, Canada, and Mexico. All of our associates have one thing in mind — helping our customers build and improve their homes. Join The Home Depot team today and see for yourself why we are consistently ranked as a top Fortune 500 company.

Company details

Company typeXLarge
IndustryRetail – Home Improvement & Building Supplies
Company size10001

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Job description

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:

  • 20% - Business Collaboration - Leverage extensive business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Provide general education on advanced analytics to technical and non-technical business partners; Deep understanding of IT needs for the team to be successful in tackling business problems; Actively seek out new business opportunities to leverage data science as a competitive advantage.
  • 30% - Project Management & Team Support - Work with project teams and business partners to determine project goals; Provide direction on prioritization of work and ensure quality of work; Provide mentoring and coaching to more junior roles to support their technical competencies; Collaborate with managers and team in the distribution of workload and resources; Support recruiting and hiring efforts for the team.
  • 35% - Solution Development - Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies; Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Prepare reports, updates and/or presentations related to progress made on a project or solution; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation.
  • 15% - Technical Exploration & Development - Guide and direct project teams in the requirements gathering, design, and development of complex applications/programs; Seek further knowledge on key developments within advanced analytics, technical skill sets, and additional data sources; Participate in the continuous improvement of predictive and prescriptive analytics by developing replicable solutions.


Direct Manager/Direct Reports:

  • This Position typically reports to Manager or Above.
  • This role has 0 direct reports.

                    
Travel Requirements:

  • Typically requires overnight travel 5% to 20% 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 18 years of age or older.
  • Must be legally permitted to work in the United States.

Preferred Qualifications:

  • Bachelors or Masters in a quantitative field  (Analytics, Computer Science, Math, Physics, Statistics, etc.) or relevant work experience.
  • 5+ years of relevant work experience
  • Demonstrated experience in predictive modeling, data mining and data analysis
  • 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 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
  • 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
     

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:

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

Minimum Years of Work Experience:

  • 4
     

Preferred Years of Work Experience:

  • 5
     

Minimum Leadership Experience:

  • No previous leadership experience


Preferred Leadership Experience:

  • No previous leadership experience
     

Certifications:

  • None


Competencies:

  • Action Oriented
  • Collaborates
  • Drives Engagement
  • Communicates Effectively
  • Customer Focus
  • Drives Results
  • Manages Conflict

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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