What are the responsibilities and job description for the Snowflake Technical Lead position at Shrive Technologies LLC?
- Design and Build Data Pipelines: Develop, automate, and maintain scalable data pipelines to bring together financial and operational data (GL, vendor invoices, headcount, budgets) from multiple enterprise sources into Snowflake.
- Model and Structure Data: Partner with architects to develop robust data models and create semantic layers, enabling user-friendly, flexible reporting and analysis.
- Implement Cost Allocation Logic: Write performant SQL and/or Python code that automates multi-layer allocation engines, cost pool processing, and service-level analytics.
- Collaborate Across Borders: Work closely with product managers, finance teams, AI/ML engineers, and QA to deliver governed, high-quality solutions on schedule.
- Automate and Optimize: Leverage workflow/orchestration tools (such as Snowflake Tasks, DBT, or Airflow) and adopt CI/CD/code versioning best practices for reliability and speed.
- Ensure Data Quality & Auditability: Implement and maintain reconciliation processes, checks, and IT controls to meet Disney’s high standards for trust, compliance, and transparency.
- Support and Evolve: Provide operational and incident support, performance tuning, and assist with continuous improvement of Enterprise Data & Analytics infrastructure.
Must Haves (Years of Experience, languages, programs, tools, etc.):
- 5 years of experience as a Data Engineer, with emphasis on cloud data platforms (Snowflake strongly preferred).
- Expertise in advanced SQL for data transformation & modeling (e.g., window functions, CTEs).
- Working experience with Python for ETL/ELT, automation, or analytics.
- Hands-on experience delivering robust, maintainable data pipelines for complex enterprise environments.
- Prior experience developing financial cost models (Financial planning, financial spend, cost allocation & recovery, etc.)
- Familiarity with workflow orchestration tools (DBT, Airflow, etc.).
- Knowledge of financial, accounting, or technology operations systems and data such as SAP, Clarity, ServiceNow, Cognos Planning and other similar systems.
- Demonstrated ability to work collaboratively in cross-functional teams.
- Strong communication skills; experience writing documentation and partnering with non-technical partners.
Nice To Haves (see above):
- Familiarity with Generative AI tools such as Snowflake Cortex AI
- Knowledge and experience working with Technology Business Management (TBM) framework and methodology
- Strong understanding of corporate finance & accounting processes
Education:
- Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.
- Model and Structure Data: Partner with architects to develop robust data models and create semantic layers, enabling user-friendly, flexible reporting and analysis.
- Implement Cost Allocation Logic: Write performant SQL and/or Python code that automates multi-layer allocation engines, cost pool processing, and service-level analytics.
- Collaborate Across Borders: Work closely with product managers, finance teams, AI/ML engineers, and QA to deliver governed, high-quality solutions on schedule.
- Automate and Optimize: Leverage workflow/orchestration tools (such as Snowflake Tasks, DBT, or Airflow) and adopt CI/CD/code versioning best practices for reliability and speed.
- Ensure Data Quality & Auditability: Implement and maintain reconciliation processes, checks, and IT controls to meet Disney’s high standards for trust, compliance, and transparency.
- Support and Evolve: Provide operational and incident support, performance tuning, and assist with continuous improvement of Enterprise Data & Analytics infrastructure.
Must Haves (Years of Experience, languages, programs, tools, etc.):
- 5 years of experience as a Data Engineer, with emphasis on cloud data platforms (Snowflake strongly preferred).
- Expertise in advanced SQL for data transformation & modeling (e.g., window functions, CTEs).
- Working experience with Python for ETL/ELT, automation, or analytics.
- Hands-on experience delivering robust, maintainable data pipelines for complex enterprise environments.
- Prior experience developing financial cost models (Financial planning, financial spend, cost allocation & recovery, etc.)
- Familiarity with workflow orchestration tools (DBT, Airflow, etc.).
- Knowledge of financial, accounting, or technology operations systems and data such as SAP, Clarity, ServiceNow, Cognos Planning and other similar systems.
- Demonstrated ability to work collaboratively in cross-functional teams.
- Strong communication skills; experience writing documentation and partnering with non-technical partners.
Nice To Haves (see above):
- Familiarity with Generative AI tools such as Snowflake Cortex AI
- Knowledge and experience working with Technology Business Management (TBM) framework and methodology
- Strong understanding of corporate finance & accounting processes
Education:
- Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.