Data Engineer - EDW Marketing & Online - INTL

Role Overview
We're hiring a Senior Data Engineer to anchor the EDW Online & Marketing organization, supporting the Nuro data warehouse and the Axien reporting web app that sits on top of it, plus brand/channel marketing integrations (Meta, Facebook, Pinterest). This is a lead-first hire: you'll go deep on the platform, own its stability, and set the technical standard for the team. Operational stability and reliability are the #1 priority — you'll keep business-critical pipelines and reporting healthy today, while helping shape the roadmap toward AI/agentic accelerators as the environment matures. We're looking for a proactive technical leader with a genuine sense of ownership and accountability — someone who drives issues and failures to resolution rather than doing the bare minimum.

The Environment
• Nuro (Online DW): A large-scale warehouse ingesting data from ~30 sources — clickstream, finance (clicks-to-sales), in-store vs. online sales comparisons — via Jenkins, Pub/Sub, into BigQuery. ~80% of producers publish through AtScale, with Excel integrations downstream.
• Axien (Online Reporting): A Python backend / Angular frontend web app powering thd.com reporting — automated report delivery (≈8 reports Monday, 1/day the rest of the week) rather than raw OLAP cubes for business users.
• Marketing: Support brand marketing to market Home Depot across largely external systems and channels (Meta/Facebook/Pinterest).

What You'll Be Doing
Incident Response, On-Call & Production Support (Top Priority)
• Act as a production support partner and technical lead alongside the team's rotational onshore and offshore support engineers.
• Monitor, triage, and resolve pipeline and job failures — including ETL/ELT job errors, data quality issues/discrepancies, and upstream/downstream dependency failures.
• Perform hands-on debugging across data platforms, system logs, and orchestration tools; execute urgent development fixes tied to high-priority production incidents.
• Own end-to-end incident management, including root cause analysis (RCA), prevention/no-repeat action plans, and clear documentation of issue details, business impact, and resolution.
• Pair with on-call engineers to offload development work, follow up on time-sensitive issues, and respond to inbound support items.
• Provide production support coverage primarily during offshore hours as part of a 24/7 rotational support model, and join incident/bridge calls during critical situations when needed.
• When production is stable, contribute to KTLO initiatives and the standard development backlog alongside the broader engineering team.

Core Data Engineering
• Design, build, and maintain robust ETL/ELT pipelines in GCP / BigQuery, integrating ~30 heterogeneous sources.
• Write advanced SQL for large-scale analytical workloads — complex joins, window functions, and performance/cost optimization on BigQuery.
• Use Python for data processing, automation, and pipeline development (including support for the Axien Python backend).
• Manage orchestration and ingestion workflows using tools like Airflow / Cloud Composer, Jenkins, and Pub/Sub.
• Ensure data quality, validation, monitoring, and production reliability; troubleshoot and support production data issues.

Semantic Layer & OLAP Modeling (High Priority)
• Design and build semantic layers / universal semantic models on top of large analytical datasets, working hands-on with AtScale (or comparable OLAP/cube tools such as SSAS).
• Develop and optimize measures, metrics, calculated fields, hierarchies, dimensions, aggregations, and performance strategies.
• Tune query performance across large datasets to support fast, interactive analytics; enable governed, self-service analytics for BI tools and business users.

Data Modeling & Analytics Architecture
• Design dimensional data models aligned to business processes; build and optimize star schemas, snowflake schemas, and fact/dimension tables.
• Translate complex business logic into scalable, reusable data models and metric layers used consistently across analytics platforms.

Technical Ownership
• Be proactive and outcome-driven: identify risks early, own failures through resolution, and mentor engineers toward a higher bar.
• Help evaluate and pilot AI/agentic accelerators as operational stability allows.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

• Hands-on expertise with AtScale or comparable OLAP/cube technologies (semantic layer / analytical modeling).
• Strong, hands-on SQL for analytics and data transformation.
• Solid Python experience in data engineering contexts.
• Deep experience with cloud data platforms — GCP / BigQuery preferred.
• Expert-level dimensional modeling and analytics-architecture understanding.
• Proven experience in production/operational support, with the ability to debug complex data issues using logs, metrics, and system traces.
• Experience conducting RCA and clearly documenting incidents.
• Comfort working in a rotational on-call/support model across onshore and offshore teams, balancing urgent fixes with ongoing development.
• Demonstrated ownership, accountability, and proactivity — a technical leader, not a bare-minimum contributor.
• Strong written and verbal communication; ability to balance technical depth with business-facing analytics needs.

• Direct experience supporting 24/7 production environments and familiarity with incident-management frameworks / post-incident best practices.
• Experience enabling analytics at enterprise scale; background partnering with BI, analytics engineering, or data science teams.
• Exposure to multiple semantic-layer/BI technologies and to CI/CD (Jenkins) for data pipelines.
• Experience with Angular (Axien frontend familiarity) and high-velocity/streaming data.
• Interest in or exposure to AI/agentic tooling for data operations.

Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.