• Expertise in complex SQL, python scripting, and performance tuning.
• Understanding of Snowflake Data engineering practices and dimensional modelling. Optimize data models for performance and scalability.
• Experience with data security and data access controls in Snowflake.
• Expertise in setting up security framework and overall governance and different compliances (Ex: SOX)
• Advanced SQL skills for building queries to create various monitors in Snowflake. Good Expertise in setting up Resource monitors for compute usage, security etc.
• Good expertise in building automations for redundant Snowflake Admin tasks.
• Expertise in handling Snowflake concepts like setting RBAC controls, scalable virtual warehouse, Resource monitors, SQL performance tuning, zero-copy clone, time travel, and automating them.
• Experience in re-clustering the data in Snowflake with a good understanding of Micro-Partitions.
• Ensure adherence to data governance standards, compliance regulations, and security policies and help in implementing the same.
• Provide expert guidance on Snowflake performance optimization, including query tuning, partitioning, clustering, and resource management. Expertise in implementing cost saving solutions on Snowflake.
• Contribute to the development of internal best practices, templates, and frameworks for Snowflake implementations.
• Engage with clients and stakeholders to provide technical recommendations for use cases, and offer insights that drive better business outcomes.
• Evaluate and integrate emerging technologies and tools that can enhance the performance and scalability of the Snowflake platform. Experience in building POC's for new concepts and features in Snowflake (Especially around AIML capabilities of Snowflake)
• Collaborate with business stakeholders, data engineers, architects, and other teams to design, optimize, and maintain scalable data architectures within Snowflake. Ensure data quality and governance best practices are followed.
• Lead and mentor junior team members, providing technical leadership and fostering knowledge sharing across teams.

Qualifications:

• Bachelors in engineering or equivalent
• 10+ years in data engineering/architecture/Administration, with at least 5+ years of hands-on experience in Snowflake architecture and administrations.

Skills:

Snowflake Expertise: In-depth knowledge of Snowflake architecture and administration, including Snowflake database design, clustering, partitioning, and query optimization. Experience in the design and implementation of data pipelines and ETL processes using Snowflake is good to have.
Data Engineering:
o Good understanding of dimensional modeling and ETL/ELT processes.
o Experience in implementing data management solutions.
o Experience in Migration processes to Snowflake from an on-premises database environment.
o Experience in designing and building manual or auto-ingestion data pipelines using Snowpipe.
o SnowSQL experience in developing stored procedures and writing queries to analyze and transform data.
o Implement best practices for data modeling, ETL/ELT pipelines, data security, and performance tuning.
o Experience in handling semi-structured data (JSON, XML), and columnar PARQUET using the VARIANT attribute in Snowflake.

Cloud Platforms: Proficiency with cloud environments like AWS, Azure, or GCP, with experience in leveraging Snowflake's native capabilities.
SQL: Advanced SQL skills for writing efficient queries, performance tuning, and data transformation.
Data Integration: Experience integrating Snowflake with other data sources and platforms, such as streaming data pipelines, APIs, and third-party tools.
Collaboration: Ability to work effectively with both technical teams and non-technical business stakeholders to translate business requirements into technical solutions.
Leadership: Strong leadership skills with the ability to mentor and guide junior team members, while ensuring successful project execution.
Problem-Solving: Excellent analytical and troubleshooting skills, with a strong ability to resolve complex technical issues.
Communication: Strong verbal and written communication skills, with the ability to present complex technical information to non-technical audiences.

Good-to-Have Skills:

• Certifications: Snowflake Certifications (e.g., Snowflake SnowPro Architect) or cloud certifications (AWS Certified Solutions Architect, Azure Data Engineer, etc.).
• Data Visualization Tools: Experience with visualization platforms such as Tableau, or Power BI.
• Data Governance: Familiarity with data governance frameworks, data privacy regulations (GDPR, CCPA, SOX), and security best practices.
• DevOps: Experience with DevOps practices for automating data pipeline deployments and management.
• Machine Learning/AI: Exposure to data science concepts or machine learning workflows integrated with Snowflake.
• Agile: Familiarity with Agile or Scrum methodologies for managing data projects.