Senior Data Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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The Home Depot

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1978

🏗️ Construction

📦 Logistics

🛒 Retail

💰 Debt Financing on 2007-07

Construction • Logistics • Retail

The Home Depot is a leading home improvement retailer, offering a wide range of building materials, home improvement products, lawn and garden products, and related services. The company operates both physical stores and an online platform, providing comprehensive solutions for DIY enthusiasts, professional contractors, and homeowners. The Home Depot is committed to diversity, equity, and inclusion, providing employment opportunities and benefits to a diverse workforce. Additionally, the company places a high emphasis on customer service and associate engagement to maintain its position as a trusted leader in the home improvement industry.

📋 Description

• Translate business requirements and build infrastructure to capture customer data • Acquire datasets aligned with business needs and develop algorithms to transform data into actionable information • Build, test, and maintain database pipeline architectures • Create data validation methods and data analysis tools • Develop, host, and maintain enterprise APIs and data solutions • Monitor, test, and validate supported products • Cleanse, organize, transform, maintain, defend, and update data structures and integrity using big-data techniques • Establish design standards and assurance processes for software, systems, and applications development • Review business and product requirements for data operations and recommend system and storage changes • Collaborate with business partners and cross-functional teams • Provide advanced analytics education to technical and non-technical partners • Guide project goals, prioritization, work quality, workload, and resources • Mentor junior roles and support recruiting and hiring • Select and apply advanced analytical methodologies • Communicate insights, recommendations, impacts, reports, updates, and presentations • Lead requirements gathering, design, and development of complex applications and programs • Develop replicable predictive and prescriptive analytics solutions • Report to a Manager or Above; no direct reports

🎯 Requirements

• Must be 18 years of age or older • Must be legally permitted to work in the United States • Minimum education: bachelor's degree program or equivalent degree in a field related to the job • Minimum 4 years of 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 pipelines in production • Experience with Python • Experience defining and capturing metadata and rules associated with ETL processes • Experience building batch and streaming pipelines • Experience writing analytical SQL queries and performance-tuning queries • Ability to stitch and maintain data from multiple sources • Ability to use JavaScript, React, Nucleus, Retina, KPI Shield, and Alert Goose • Ability to produce tags for site data • Ability to use Python and Google BigQuery to stitch and enrich raw data from multiple sources • Experience with PySpark, AirFlow, and DataProc • Ability to optimize pipeline runtime and reduce slot/storage consumption costs • Ability to prioritize requests and manage a product roadmap • Experience coaching junior engineers • Strong verbal and written communication skills

🏖️ Benefits

• Overnight travel typically required 5% to 20% of the time