
Data Architect Specialist
6 days ago
Company Overview:
S&P Global, Inc. is the world's foremost provider of credit ratings, benchmarks, and analytics in the global capital and commodity markets.
The company's divisions include S&P Global Ratings, S&P Global Market Intelligence, S&P Dow Jones Indices, and S&P Global Platts.
S&P Global empowers organizations to make informed decisions with essential intelligence.
About the Role:
We are seeking a highly skilled Data Engineer II to join our dynamic Data Engineering Team.
This team thrives on collaboration, working closely with business and technical stakeholders to drive impactful data initiatives.
As a Data Engineer II, you will design and implement scalable data architectures that align with strategic objectives, enhancing overall business performance.
You will utilize your expertise in Snowflake, Python, and cloud technologies to ensure robust data security and integrity.
Drive innovation by integrating AI-driven models and optimizing data workflows, thereby improving data processing efficiency and supporting informed decision-making across the organization.
Key Responsibilities:
- Design and implement scalable and efficient data systems, ensuring robust data architecture.
- Develop innovative data products that align with business goals and enhance data accessibility.
- Ensure data integrity and confidentiality through expert application of data security and encryption protocols.
- Leverage cloud technologies, particularly AWS, to optimize data operations and enhance performance.
- Implement and manage RBAC security models within Snowflake to maintain secure data environments.
- Collaborate across business and technical teams to ensure effective communication and project delivery.
- Manage large-scale data projects from inception to completion, ensuring timely and successful outcomes.
Requirements:
- Bachelor's degree in software engineering, Computer Science, or a related field, or 5+ years of experience in data engineering.
- 5+ years of experience working with Snowflake in a data engineering capacity.
- Strong proficiency in data architecture and demonstrated experience in data product development.
- Advanced proficiency in Python and SQL for data transformation and analytics.
- Deep understanding of RBAC security models and secure data connection protocols (JDBC, ODBC, etc.).
- Excellent communication skills for effective collaboration across diverse teams.
- Exposure to systems integrations for seamless data interoperability.
- Proficiency in query optimization and algorithmic efficiency.
PREFERRED QUALIFICATIONS:
- Knowledge of machine learning for integrating basic models into data processes.
- Strong collaborative skills and the ability to work effectively in team-oriented environments.
- Experience with Cortex AI, LLM tools, and developing Streamlit applications.
- Familiarity with data governance, security, and compliance best practices.
- Certifications in Snowflake, data engineering, or related fields.
- Experience with data visualization tools like Tableau or Power BI, and ELT/ETL tools such as Informatica.
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