Data Warehouse & Integration Engineer

About Goods & Services
  
Goods & Services is a product design and engineering company. 

We solve mission-critical challenges for some of the world’s largest enterprises, with deep expertise in highly regulated industries—including life sciences and financial services. Our design-led approach allows us to apply cutting-edge capabilities in AI, Data and Hardware Engineering to companies of any size. 

Headquartered in the United States, we operate regional development centers in Mexico and the United Kingdom. This global footprint—anchored by our nearshore model—enables us to deliver at scale with the speed, efficiency, and cultural alignment our clients expect.

At Goods and Services, we value diversity and are committed to creating an inclusive workplace where everyone can thrive. We are proud to be an Equal Opportunity Employer and welcome qualified applicants from all backgrounds.

About the job
  
Goods & Services is looking for a Senior Data Warehouse and Integration Engineer responsible for database engineering, data warehouse architecture and support, data integration, reporting support, production troubleshooting, and technical delivery. This role requires someone who can independently own complex DB/data work from investigation and design through production completion and ongoing support. The biggest need is database/data integration ownership and production troubleshooting, followed by data warehouse architecture and reporting. The role needs someone to be comfortable with the existing on-prem/Microsoft environment while also helping us move toward more modern Azure-based solutions.

What you’ll do:

• Design, develop, maintain, and troubleshoot SQL Server databases, stored procedures, views, jobs, and related database objects.
• Design and support enterprise data warehouse architecture, data models, schemas, and data flows.
• Evaluate and improve data warehouse structure, scalability, performance, and maintainability.
• Support data warehouse production operations, including failures, performance issues, data quality issues, and downstream dependencies.
• Support and troubleshoot SSIS, ETL processes, integrations, APIs, files, feeds, and scheduled data processes.
• Design reliable data movement between source systems, staging layers, data warehouse environments, and reporting platforms.
• Investigate production database, data warehouse, integration, and reporting issues and drive them to root cause and resolution.
• Reconcile report and data discrepancies against source systems.
• Review database, warehouse, and integration changes for dependencies and downstream impact.
• Support query performance, data integrity, reliability, and production stability.
• Define and execute technical testing for database, warehouse, and integration changes.
• Support DEV, TEST/UAT, and PROD deployments, including rollback planning where needed.
• Build monitoring, failure detection, retry, and recovery processes for automated integrations and warehouse processes.
• Maintain documentation for critical databases, warehouse architecture, integrations, jobs, reports, data flows, and support procedures.
• Work directly with Development, BA, PM, Applications, Infrastructure, and Support teams.
• Maintain clear status, target dates, blockers, risks, and next steps for assigned work.
• Escalate risks and dependencies early instead of allowing work to remain indefinitely in investigation.
• Ensure completed technical work is tested, validated, documented, deployed, and supportable.

What you’ll need:

• Strong Microsoft SQL Server experience
• Advanced T-SQL
• Data warehouse design and architecture
• Dimensional modeling and enterprise data modeling
• Data warehouse support and production troubleshooting
• Stored procedures, views, functions, and SQL Agent jobs
• SSIS / SSISDB or equivalent ETL experience
• ETL architecture and data pipeline design
• Data integration and troubleshooting
• Data reconciliation and reporting support
• Query performance and optimization
• Production database support
• Root cause analysis
• Data lineage and dependency analysis
• APIs, files, feeds, and system integrations
• Production deployment and change management
• Azure data services where applicable

Nice to have:

• Enterprise data warehouse environments
• Complex operational, financial, or regulatory reporting
• Multi-system integrations
• Large production SQL environments
• Data warehouse modernization or redesign initiatives