{"id":44304,"url":"https://alion.io/job/the-home-depot-online-data-engineer","title":"Online Data Engineer","company":{"id":13463,"name":"The Home Depot","domain":"homedepot.com","url":"https://alion.io/company/homedepot","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":82,"open_postings":98,"ghost_share":0,"stale_share":0.714,"repost_share":0,"time_to_fill_p50_days":35,"computed_at":"2026-10-28T05:59:10Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Atlanta, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":92000,"max_usd":201000,"period":"year","method":"role_country_seniority_unknown","sample_n":3718},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Hadoop","optional":false},{"name":"CI/CD","optional":true},{"name":"ETL/ELT","optional":true},{"name":"Google BigQuery","optional":true},{"name":"JavaScript","optional":true},{"name":"pySpark","optional":true},{"name":"Python","optional":true},{"name":"React.js","optional":true},{"name":"Spark","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-08-06T00:00:00Z","employer_posted_date":"2026-08-06","last_verified_at":"2026-10-28T22:17:05Z","board_verified":true,"closed_at":null,"days_open":84,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":84},"description":"With a career at The Home Depot, you can be yourself and also be part of something bigger.\nPosition Purpose:\nOnline 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.\nOur 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.\nThe Data Engineer position applies data extraction, transformation and loading techniques in order to connect large data sets from a variety of sources. They create data collection frameworks for structured and unstructured data and develops and maintain infrastructure systems (e.g., data warehouses, data lakes) including data access APIs. Data Engineers prepare and manipulate data using Hadoop or equivalent MapReduce platform.\nKey Responsibilities:\n10% - Business Collaboration - 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.\n20% - Project Management & Team Support - 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.\n55% - Solution Development - 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.\n15% - Technical Exploration & Development - 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.\nDirect Manager/Direct Reports:\nThis position reports to the Manager or Above\nThis position has 0 direct reports\nTravel Requirements:\nNo travel required.\nPhysical Requirements:\nMost 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.\nWorking Conditions:\nLocated in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.\nMinimum Qualifications:\nMust be 18 years of age or older.\nMust be legally permitted to work in the United States.\n Preferred Qualifications:\nBachelors or Masters in a quantitative field (Analytics, Computer Science, Math, Physics, Statistics, etc.) or relevant work experience.\nDemonstrated knowledge developing and testing ETL jobs/pipelines, configuring orchestration, automated CI/CD, writing automation scripts, and supporting the pipelines in production.\nExperience in high-level programming languages such as Python\nExperience defining and capturing metadata and rules associated with ETL processes\nExperience building Batch and Streaming pipelines\nExperience writing analytical SQL queries\nAbility to stich and maintain data from multiple sources\nAbility to use JavaScript, Front-end development frameworks (React, Nucleus), and QA apps (Retina, KPI Shield, Alert Goose)\nAbility to produce tags for site data\nAbility to code in Python, Google BigQuery to stitch and enrich the raw data from multiple sources\nAbility to use PySpark, AirFlow, and DataProc to engineer and automate data flows pipelines\nAbility to optimize the pipelines run time and lower the cost on slots/storage consumption\nAbility to prioritize requests and manage a product roadmap\nStrong verbal and written communications skills at all levels\nMinimum Education:\nThe 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.\nPreferred Education:\nThe 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.\nMinimum Years of Work Experience:\n2\nPreferred Years of Work Experience:\n3\nMinimum Leadership Experience:\nNo previous leadership experience\nPreferred Leadership Experience:\nNo previous leadership experience\nCertifications:\nNone\n Competencies:\nAction Oriented\nCollaborates\nCommunicates Effectively\nCustomer Focus\nDrives Results","description_format":"text","description_chars":5461,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Commerce","Retail & Shop Systems"],"lifecycle":[{"event":"open","at":"2026-08-06T00:00:00Z"}],"visa":[],"liveness":{"score":7,"band":"cold","label":"Long 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