Cheesy joke to get you to smile:

Two SQL transactions ask a minister to marry them, but the minister replies, "Only if you're willing to commit."

Summary:

We are seeking a hands-on Data Engineer who is skilled in building complex systems beyond just writing queries. This role focuses on SQL Server in both Linux and Windows environments and requires versatility across various tools, including PowerShell, APIs, Python, and emerging AI/LLM technologies. If you enjoy stretching your expertise beyond SQL and want to contribute to innovative solutions, this position is for you. The role is for one of our North American clients with proprietary software for the insurance industry.

Responsibilities:

• Design, build, and optimize complex SQL Server solutions, emphasizing performance tuning, indexing, and data modeling.
• Manage relational and semi-structured data, including JSON stored in SQL Server and multi-dimensional datasets.
• Query and transform JSON using native SQL Server tools, such as OPENJSON and JSON_VALUE.
• Use PowerShell, SQL Server tools, and scripting to automate processes.
• Enhance functionalities by integrating with APIs and external systems.
• Address problems comprehensively, focusing on end-to-end solutions beyond the database layer.
• Operate within a complex, multi-system application environment, avoiding isolated reporting or analytics tasks.
• Explore and implement LLM-driven workflows, including prompting and structured outputs.
• Continuously enhance efficiency by replacing manual processes with automation.

Required Skills:

• Proficient in SQL Server, including query performance, indexing, and data modeling.
• Experience handling JSON in SQL Server and managing hybrid data models.
• Experience with PowerShell or similar scripting languages for automation purposes.
• Ability to work across multiple systems, including databases, APIs, and services.
• Proven ability to deliver effective solutions in a timely manner.

Preferred Skills:

• Background in smaller teams with end-to-end system ownership.
• Experience in complex application environments rather than isolated reporting or analytics settings.
• Capability to navigate and solve problems without detailed requirements.
• Experience in insurance, financial services, or other regulated, transaction-heavy domains.