Note: The job is a remote job and is open to candidates in USA. The Home Depot is seeking a Senior Data Engineer to build and maintain data infrastructure, pipelines, APIs, and enterprise data solutions. The role guides solution development, advanced analytics, project teams, data quality processes, and continuous improvement of predictive and prescriptive analytics.
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
- This Position typically reports to Manager or Above
- This role has 0 direct reports
- Typically requires overnight travel 5% to 20% of the time
- 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
- Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable
- Must be 18 years of age or older
- Must be legally permitted to work in the United States
Skills
- Must be 18 years of age or older
- Must be legally permitted to work in the United States
- 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
- 4
- No previous leadership experience
- 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
- 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
- 5
- No previous leadership experience
Benefits
- Remote work arrangement
Company Overview