Data Engineer (Warehouse, BI & SQL DBA)

Barrett-Jackson Auction Co, LLC•Scottsdale, AZ

3d•Onsite

About The Position

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/Lakehouse (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

6+ years of hands-on experience in data engineering and/or data warehouse engineering, including building production-grade pipelines and curated datasets.
4+ years administering and tuning SQL Server and/or Azure SQL (query optimization, indexing, security, backup/restore, and maintenance).
Strong proficiency with T-SQL, relational data modeling, and performance tuning (execution plans, statistics, partitioning, and concurrency patterns).
Experience building ELT/ETL with Azure Data Factory/Synapse Pipelines and/or Fabric Data Factory; familiarity with event/file-based ingestion patterns.
Experience designing and operating a modern warehouse/lakehouse using Azure Synapse and/or Microsoft Fabric (Lakehouse/Warehouse, notebooks/Spark, and orchestration).
Strong understanding of data warehouse concepts and modeling techniques (Kimball dimensional modeling, SCD, data marts, and semantic layer alignment).
Power BI experience supporting enterprise reporting (datasets/semantic models, refresh strategies, performance optimization, and workspace governance).
Experience with Azure security and identity patterns (Azure AD, managed identities, Key Vault, RBAC) and protecting sensitive data (PII) end-to-end.
Hands-on experience with DevOps practices: Git branching, code reviews, CI/CD, and automated deployments (Azure DevOps and/or GitHub).
Strong troubleshooting skills across data pipelines, databases, and BI; ability to communicate clearly with technical and non-technical stakeholders.
Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent experience.

Nice To Haves

Experience using AI-assisted tools to support database administration, SQL development, reporting, troubleshooting, and workflow optimization is preferred.

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/Lakehouse, including dimensional modeling (star/snowflake), incremental loads, historization (SCD), and semantic layer alignment for BI.
Administer and optimize Azure Synapse and/or Microsoft Fabric (Lakehouse/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, auditability) across databases, lakehouse/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 runbooks, 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.