IT Data Platform Engineer

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🕒 May 14

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Logo of Evergen (Formerly RTI Surgical)

Evergen (Formerly RTI Surgical)

501 - 1000 employees

Founded 1998

🧬 Biotechnology

⚕️ Healthcare Insurance

💊 Pharmaceuticals

Biotechnology • Healthcare Insurance • Pharmaceuticals

Evergen is a world-class Contract Development and Manufacturing Organization (CDMO) with a 25-year history of innovation in regenerative biomaterials. Formerly known as RTI Surgical, Evergen partners with innovative companies to accelerate the design, development, and manufacturing of life-changing regenerative medicine therapies. Their commitment to quality and safety has led to over 17 million life-enhancing implants, reflecting their dedication to providing patient-centric biomaterial solutions for effective healing.

📋 Description

• Own and manage Fivetran connectors across all source systems • Configure and monitor sync schedules, column exclusions, and incremental load strategies • Troubleshoot connector failures and proactively manage schema drift • Maintain and extend our dbt project across three layers • Write and optimize SQL models using incremental merge strategies and watermark patterns • Manage end-to-end pipeline scheduling and monitoring • Maintain the integration between Fivetran, dbt, and Power BI dataset refresh triggers • Build and maintain alerting for pipeline failures • Manage Snowflake environments including databases, schemas, and roles • Implement and maintain access controls and role-based permissions • Partner with Finance, Sales, and Operations teams to understand reporting requirements

🎯 Requirements

• 3 to 5 years of experience in data engineering, analytics engineering, or a closely related role • Hands-on experience with dbt (Core or Cloud) including incremental models, tests, macros, and documentation • Proficiency with Snowflake including schema design, query optimization, warehouses, and role-based access control • Experience with a managed ingestion tool such as Fivetran and dlt including connector configuration and monitoring • Strong SQL skills with the ability to write and debug complex analytical queries • Familiarity with ELT pipeline patterns and medallion-style data warehouse architecture • Experience troubleshooting pipeline failures independently and communicating issues clearly to non-technical stakeholders • Comfort working autonomously in a small team environment with limited oversight

🏖️ Benefits

• Current or future sponsorship is not available for this role

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