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Capgemini Engineering is hiring Solution Data Architect

➡️ Apply here: Solution Data Architect

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**About The Job You’re Considering**

An AWS & Snowflake Data Solution Architect is responsible for designing, implementing, and managing data solutions that leverage both AWS and Snowflake platforms. Here are some key responsibilities and requirements typically found in this role:

**Your role**

* Solution Design: Architect end-to-end data warehousing and analytics solutions, integrating Snowflake with AWS services.
* Technical Leadership: Provide technical guidance and leadership in the design and implementation of data solutions.
* Data Integration: Integrate data from various sources, ensuring data quality and consistency.
* Performance Optimization: Optimize data processing performance and troubleshoot issues.
* Security: Implement data security measures and ensure compliance with data governance policies.
* Collaboration: Work closely with data engineers, data scientists, and other stakeholders to understand data requirements and deliver solutions.
* Technical Demonstrations: Lead technical demonstrations, presentations, and proof-of-concepts (POCs) to showcase the value proposition of Snowflake and AWS

**Your Skills And Experience**

* Experience: 5-10 years of experience in data architecture, cloud solutions, or data warehousing, with significant experience in both AWS and Snowflake.
* Technical Skills: Proficiency in SQL, data modeling, ETL processes, and cloud platforms (AWS and Snowflake). Experience with AWS services like EC2, S3, Redshift, Lambda, and API Gateway.
* Tools: Familiarity with DevOps tools like Git, Jenkins, and CI/CD pipelines.
* Data Processing: Experience with big data technologies like Spark, Hive, and Kafka.
* Problem-Solving: Strong analytical and problem-solving skills.
* Communication: Excellent communication skills to collaborate with cross-functional teams.
* Certifications: Relevant certifications in AWS (e.g., AWS Certified Solutions Architect) and Snowflake.
* Agile Methodologies: Experience with Agile, Scrum, and other project management methodologies.
* Advanced Analytics: Knowledge of machine learning and advanced analytics techniques

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