Data Engineer (Warehouse, BI & SQL DBA)

Job Title: Data Engineer (Warehouse, BI & SQL DBA) Scottsdale, AZ , United States - 85250 Position Purpose: We are seeking a Data Engineer (Warehouse, BI & SQL DBA) to join our Scottsdale-based team and own our end-to-end Microsoft data platform—from database design and administration, through reliable data pipelines, into a governed enterprise Data Warehouse/Lake-house (Azure Synapse and/or Microsoft Fabric), and ultimately enabling analytics and reporting in Power BI. This role blends hands-on SQL Server/Azure SQL engineering and DBA responsibilities with modern ELT/ETL development, dimensional modeling, performance tuning, security, and data governance. You will partner closely with application teams, business stakeholders, and analytics users to deliver trusted, well-documented datasets and scalable solutions that support operational and strategic decision-making. Requirements Key Responsibilities: • Design, implement, and administer SQL Server and Azure SQL databases, including schema design, indexing strategies, constraints, and data integrity controls. • Own core DBA functions: backup/restore, HA/DR, patching and upgrades, capacity planning, monitoring/alerting, and routine maintenance. • Build and optimize ELT/ETL pipelines using Microsoft tooling (e.g., Azure Data Factory/Synapse Pipelines and/or Fabric Data Factory), integrating data from on-prem and cloud sources. • Develop scalable transformation patterns using T-SQL and Spark (where applicable), implementing repeatable, testable data-processing frameworks. • Design and manage the enterprise Data Warehouse/Lake-house, including dimensional modeling (star/snowflake), incremental loads, historization (SCD), and semantic layer alignment for BI. • Administer and optimize Azure Synapse and/or Microsoft Fabric (Lake house/Warehouse), including workspace organization, resource governance, and performance/cost tuning. • Enable Power BI reporting by delivering curated datasets, developing and supporting semantic models, and partnering with analysts on performance, refresh strategies, and best practices. • Implement data quality, reconciliation, and observability (logging, lineage, SLAs), and drive root-cause analysis for data issues across pipelines and reporting. • Establish and enforce security and governance controls (RBAC, least privilege, encryption, PII handling, audit ability) across databases, lake house/warehouse, and BI. • Automate deployments and operations using Git-based workflows and CI/CD (Azure DevOps/GitHub), including infrastructure-as-code where appropriate. • Create technical documentation for data models, source-to-target mappings, operational run books, and support procedures. • Collaborate with application engineering, product, and business stakeholders to translate requirements into reliable data products and deliver iteratively in an Agile environment.