Online Data Engineer

Home Depot • Atlanta, GA

47d

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. The 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.

Requirements

• 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.

Nice To Haves

• 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

Responsibilities

• 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.
• 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.
• 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.
• Techical 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Building Material and Garden Equipment and Supplies Dealers