Lead Data Engineer – Finance Analytics, Automation & AI (AAA)

The Home Depot

80d • $90 - $16,000

About The Position

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.

Requirements

• Must be 18 years of age or older.
• Must be legally permitted to work in the United States.
• Minimum of 5 years of work experience in a related field.
• Bachelor's degree or equivalent degree in a field of study related to the job.

Nice To Haves

• Masters in a quantitative field (Analytics, Computer Science, Math, Physics, Statistics, Management, etc.) or relevant work experience.
• Ability to stitch 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.
• Demonstrated expertise of how to model and mine data.
• Demonstrated expertise of how to build and maintain data pipelines.
• Demonstrated knowledge of the business to support future data needs and proactive data management.

Responsibilities

• Leverage extensive business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Partner with Other Orgs to understand potential for new tools and ways to maintain technical agility for advanced analytics.
• Lead and manage large and complex projects and teams; Provide direction on prioritization of work and ensure quality of work; Collaborate with managers and team in the distribution of workload and resources; Serve as a technical subject matter expert (SME) on both predictive and prescriptive analytics; Drive effective Agile project delivery protocols to assure we gather and surface reliable, actionable enterprise level analytics; Ensure the team comprehends and applies the established processes and standards and mentor team on development.
• Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation; Develops solutions to transform data into useful, actionable information.
• Guide and direct project teams in the requirements gathering, design, and development of complex applications/programs; Provide technical education on advanced analytics to analytics community; Drive analytics teams to get matured in predictive and prescriptive analytics.

Benefits

• 401k
• health_insurance
• dental_insurance
• vision_insurance
• paid_holidays
• employee_discount_programs

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Bachelor's degree
• Number of Employees: 5,001-10,000 employees