Data Platform Engineer

The Data Platform Engineer is responsible for designing, supporting, and modernizing the company’s enterprise data platforms across on-premises and cloud environments. This role combines strong database engineering experience with modern cloud data services, data integration, automation, analytics enablement, and AI-ready data management. This position will support existing Microsoft SQL Server environments while helping transition the organization toward scalable, secure, and governed data platforms using Microsoft Azure, Microsoft Fabric, and related technologies. The role will collaborate with infrastructure, application development, analytics, and business teams to improve data reliability, accessibility, performance, and overall platform maturity., * Design, build, and support modern data platforms across SQL Server, Azure, Microsoft Fabric, and hybrid environments.

• Support and modernize SQL Server environments through performance tuning, indexing, query optimization, backups, recovery, security, and availability.
• Implement and support Azure data services, including Azure SQL Database, Azure SQL Managed Instance, Azure Data Factory, Azure Storage, Azure Key Vault, and related services.
• Support Microsoft Fabric capabilities, including lakehouses, warehouses, pipelines, semantic models, notebooks, and Power BI-ready datasets.
• Build and maintain data pipelines, ETL/ELT processes, integrations, and data movement patterns across internal systems, cloud platforms, vendor systems, and reporting tools.
• Assist with data architecture decisions for relational databases, data warehouses, lakehouses, APIs, analytical models, and cloud-native data services.
• Improve data quality through validation, reconciliation, monitoring, exception reporting, and documentation of trusted data sources.
• Collaborate with application development teams on database design, data access patterns, schema changes, integration methods, and performance optimization.
• Support analytics, reporting, automation, and AI initiatives by preparing clean, governed, and reliable enterprise data and designing secure data access patterns.
• Automate and support data platform operations using T-SQL, PowerShell, Python, Azure CLI, REST APIs, and CI/CD practices for database objects, pipelines, scripts, and cloud configurations.
• Monitor and troubleshoot data platforms, pipelines, and integrations for performance, reliability, cost, and security, performing root cause analysis and recommending long-term corrective actions.
• Document data flows, platform architecture, operational procedures, support runbooks, and technical standards, and evaluate new Microsoft data platform capabilities for adoption.

Do you have experience in System tuning?, Do you have a Bachelor’s degree?, Education/Experience: Bachelor’s degree in computer science, Information Technology, Data Engineering, Information Systems, or related field preferred. 5+ years of experience in database engineering, data platform engineering, data engineering, cloud data services, or a related technical role. Strong experience with Microsoft SQL Server, T-SQL, query tuning, indexing, stored procedures, performance troubleshooting, and relational database design. Experience with Azure data services such as Azure SQL, Azure Data Factory, Azure Storage, Azure Synapse, Azure Key Vault, or similar technologies. Experience building or supporting data pipelines, integrations, ETL/ELT workflows, reporting datasets, or analytical data platforms. Experience with Microsoft Fabric, Power BI, lakehouse, warehouse, or semantic modeling concepts preferred. Experience supporting analytics, automation, AI-readiness, enterprise search, or governed data access initiatives preferred. Equivalent combination of education and experience will be considered. Computer Skills: To perform this job successfully, an individual must be proficient with Microsoft Office programs such as Office 365 and Word. * Microsoft SQL Server * T-SQL * Azure SQL Database / Azure SQL Managed Instance * Azure Data Factory * Microsoft Fabric * Azure Storage / Data Lake concepts * Azure Synapse Analytics * Power BI semantic models * Data modeling * ETL/ELT design * Data quality validation * Python or PowerShell * Git * Azure DevOps or GitHub Actions * CI/CD practices * Infrastructure as code concepts * API-based data integrations * Monitoring and observability * Database security and access control * Cloud-native data architecture * AI-ready data architecture preferred Certificates and Licenses: Certifications are not required but are preferred. Relevant certifications may include: * Microsoft Certified: Azure Data Engineer Associate * Microsoft Certified: Azure Database Administrator Associate * Microsoft Certified: Fabric Analytics Engineer Associate * Microsoft Certified: Azure Solutions Architect Expert * Microsoft Certified: Power BI Data Analyst Associate * Microsoft Certified: Azure AI Engineer Associate Supervisory Responsibilities: This position will not have supervisory responsibilities.

Pulled from the full job description

• 401(k) matching
• Paid sick time
• Life insurance
• Employee assistance program
• Paid holidays, The hiring pay range provides a good faith estimate of the salary or hourly wage that Living Spaces expects to pay for the position upon hire. Pay will be determined by several factors, including, but not limited to: applicant’s education, relevant work experience, knowledge, applicable and relevant skills and abilities, market demand, Company budget, as well as internal equity and alignment with geographic market data. Living Spaces reserves the right to modify this page at any time.

Compensation: -

Overtime pay is available for eligible, non-exempt Team Members. Reimbursement for expenses as required by applicable law and Company policy. Retail, Guest Services and Distribution Center Team Members are eligible to receive team bonus based on meeting specific goals and KPI’s.

Additional available benefits upon meeting eligibility requirements include:

• Medical (full-time only)
• Dental (full-time only)
• Vision (full-time only)
• 401(k) with Company match (full and part-time)
• Vacation (full-time only or as otherwise required by applicable law)
• Paid Sick Leave (full and part-time)
• Flex or Health Spending Account (for eligible full-time only)
• Employee Assistance Program (full and part-time)
• Holiday pay (full-time only)
• Life insurance (full-time only)