Data Architect - Snowflake DB

Description :

- SQL- Advanced to Expert

- Snowflake- Intermediate +

- AWS- Advanced (Data engineering scope)

- DWH-Intermediate +

- Python- Intermediate +

- CI/CD- Intermediate +

- Familiarity with API Development, reporting tools( Power-BI) will help.

Job Description :

- Serve as a Senior Technical Lead, responsible for designing, implementing, and maintaining complex data engineering solutions using Snowflake, Snowpipe, and SnowSQL.

- Collaborate with cross-functional teams to understand business requirements, and translate them into efficient and scalable data architecture and ETL processes.

- Develop and optimize advanced SQL queries and data transformation scripts, ensuring high-performance and fault-tolerant data pipelines.

- Provide technical leadership and mentorship to junior team members, guiding them in best practices and continuous improvement of the data engineering ecosystem.

- Demonstrate expertise in AWS services, leveraging them for data ingestion, processing, and storage to build robust and scalable data platforms.

- Possess strong working knowledge of data warehousing concepts, including dimensional modeling, ETL processes, and data optimization techniques.

- Proficient in Python programming, leveraging it for data manipulation, automation, and integration with various data sources and reporting tools.

- Familiarize with CI/CD practices and tools to ensure seamless deployment and integration of data engineering solutions.

- Engage with stakeholders, provide insights, and develop customized reporting solutions using tools like Power BI.

- Maintain a strong understanding of API development and integration to facilitate data exchange and connectivity across systems.

Qualifications :

- 8 to 12 years of experience in data engineering, with a strong focus on Snowflake, Snowpipe, and SnowSQL.

- Advanced to expert-level proficiency in SQL, with the ability to write complex and optimized queries.

- Intermediate-level expertise in Snowflake, including the ability to design and implement scalable data solutions.

- Advanced-level experience in AWS services, particularly for data engineering use cases.

- Intermediate-level understanding of data warehousing concepts and practices.

- Intermediate-level proficiency in Python programming, with the ability to develop data-centric applications and scripts.

- Intermediate-level experience in CI/CD practices and tools, ensuring seamless deployment and integration of data engineering solutions.

- Familiarity with API development and integration, as well as reporting tools like Power BI, is preferred.