PREFERRED QUALIFICATIONS:

• Strong SQL skills: Proficient in writing, optimizing, and troubleshooting T-SQL for SQL Server or PL/SQL for Oracle.
• Experience with SQL Server (2016+ preferred), including SSIS, SSMS, and performance tuning tools.
• Exposure to cloud data platforms, such as Azure Data Lake, Azure Databricks, Synapse Analytics, or Microsoft Fabric is a plus.
• ETL/ELT pipeline design and implementation experience.
• Understanding of data warehousing concepts and dimensional modeling (Kimball, Inmon, etc.).
• Problem-solving mindset with a keen attention to detail.
• Experience with Python or Scala for data engineering tasks is a plus.
• Experience with CI/CD practices in a data engineering context.
• Familiarity with data governance, data quality, and data cataloging tools.
• Previous experience in a regulated industry (finance, healthcare, etc.) is a plus.

MINIMUM QUALIFICATIONS:

• College Degree or equivalent required (ideally in Computer Science, Information Systems, Engineering, or related field)
• 6 years related experience as a Data Engineer, ETL Developer, or similar role.
• Expert technical knowledge
• Knowledge of industry regulations
• Ability to lead and coordinate the team activities of others
• Ability to formulate, document and recommend new policies and procedures
• Able to work in and lead a team
• Demonstrated ability to communicate verbally and in writing throughout all levels of an organization, both internally and externally
• Ability to travel as required by business and on-call availability
  

  LI-MM2 #LI-Hybrid

CBIZ.Jobs Category: Corporate

• Design, build, and maintain data warehouses and lakehouses to support scalable, reliable analytics and reporting solutions.
• Develop and optimize complex SQL queries for ETL/ELT processes, data validation, and analytics workloads.
• Diagnose and troubleshoot data pipeline, SQL, and ETL errors to ensure high data quality and reliable data flows.
• Collaborate with stakeholders to understand data requirements and implement solutions that meet business needs.
• Integrate with cloud data platforms (Azure Data Lake, Databricks, Synapse, Microsoft Fabric) as needed for modern data architectures.