Online Data Engineer

Summary

The Home Depot is a leading home improvement retailer, and they are seeking an Online Data Engineer to translate business requirements into actionable data solutions. The role involves developing algorithms, maintaining database architectures, and collaborating with cross-functional teams to enhance data-driven decision-making processes.

Responsibilities

• Incorporate business knowledge into solution approach. Effectively develop trust and collaboration with internal customers and cross-functional teams; Work with project teams and business partners to determine project goals
• Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Present recommendations in a confident manner in order to influence execution of recommendation. 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
• Develops algorithms to transform data into useful, actionable information . Design and develop algorithms and models to use against large datasets to create business insights; Participates in large data analytics project teams by serving as a lead for analytics projects; May lead small projects and work independently on solution development. Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies
• 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

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
• 2 years of work experience
• No previous leadership experience
• Bachelors or Masters in a quantitative field (Analytics, Computer Science, Math, Physics, Statistics, etc.) or relevant work experience
• Demonstrated knowledge 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
• Experience writing analytical SQL 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
• 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
• Strong verbal and written communications skills at all levels

Qualifications

Must Haves

• 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
• 2 years of work experience
• No previous leadership experience

Nice to Haves

• Bachelors or Masters in a quantitative field (Analytics, Computer Science, Math, Physics, Statistics, etc.) or relevant work experience
• Demonstrated knowledge 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
• Experience writing analytical SQL 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
• 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
• Strong verbal and written communications skills at all levels