Sr Data Engineer

Build governed, reusable analytical data products that power reporting, self-service analytics, dashboards, and AI-assisted decision-making at Lowe’s.

Responsibilities

• Translate business questions, reporting requirements, and metric definitions into reusable analytical components such as data models, semantic layer objects, explores, measures, dimensions, and certified datasets.
• Apply advanced SQL, data modeling, and domain expertise to create reliable analytical logic across enterprise data platforms.
• Develop governed semantic layer assets and self-service explores to reduce ad hoc data pulls and support scalable reporting.
• Design, build, validate, and maintain analytical assets used for dashboards, self-service reporting, AI-assisted analysis, and decision-making.
• Run data validation, reconciliation, quality checks, and performance reviews to ensure outputs are accurate, consistent, and scalable.
• Collaborate with development teams to test, deploy, monitor, and improve analytical assets, semantic layer updates, tracking logic, and integrations.
• Create data engineering project plans including scope, requirements, technical approach, dependencies, timelines, risks, and expected outcomes.
• Coordinate with Analytics, Product, Engineering, Data Engineering, and business teams on definitions, source logic, data lineage, grain, joins, filters, attribution, and usage expectations.
• Communicate data model design, semantic logic, project status, risks, issues, and recommendations to stakeholders.
• Support dashboard rationalization by identifying duplicate logic, low-value reporting, manual workflows, and opportunities to automate, productize, transition, or retire assets.
• Enable trusted Newton Analyst and AI-assisted analytics by validating results and creating governed AI-ready data assets with reliable metric access.
• Recommend improvements across data quality, metric consistency, self-service adoption, reporting scalability, and business impact.
• Maintain documentation covering metric definitions, transformation logic, source-to-target mapping, lineage, assumptions, limitations, and usage guidance.
• Mentor Associate Data Engineers, Analysts, and other team members on SQL, data modeling, semantic layers, validation, documentation, and engineering best practices.
• Measure impact through reduced manual data pulls, improved dashboard performance, increased self-service adoption, stronger metric consistency, and greater trust in analytical outputs.

Requirements

• Bachelor’s degree in engineering, computer science, computer information systems (CIS), or related field, or equivalent years of experience in lieu of education (if applicable).
• 5 years of experience in data, business intelligence, platform engineering, data warehousing/ETL, or software engineering.
• 4 years of experience working on projects implementing solutions that follow development life cycles (SDLC).
• 3 years of experience with object-oriented programming/structure programming, SQL, and scripting.
• 3 years of experience in big data technology.
• 3 years of experience in cloud-based big data technologies.

Technologies

• SQL
• LookML
• dbt
• Python
• R
• Alteryx
• Knime
• SAS
• Newton Analyst

Benefits

• 401k with up to 4.25% match
• Discounted Employee Stock Purchase Plan (15% discount of strike price)
• Tuition-Free Education
• 10-week Maternity/Parental Leave
• 10% Associate Discount

Where You’ll Be

• Relocation required for Associates to the Lowe’s Tech Hub Charlotte, NC to foster collaboration and support.
• Office work requirement: 5 days per week at the Charlotte Tech Hub office location.
• Most business meetings planned around the Eastern time zone.

Preferred Skills / Education

• Master’s degree in Business, Engineering, Computer Science, Data Science, Statistics, Information Systems, Economics, or related field.
• Experience with semantic modeling, governed datasets, LookML, dbt, advanced SQL, and cloud data platforms.
• Experience with data modeling, optimization, data quality, lineage, testing, CI/CD, and reporting automation.
• Experience with self-service and AI-assisted analytics, metric governance, and tools such as Python, R, Alteryx, Knime, or SAS.
• Experience delivering complex data solutions across Product, Engineering, Analytics, and business teams, including project management and large-scale retail data.

Location: Charlotte, NC (onsite) | Compensation: USD 95,100 - 180,700 per year