Data Solutions Architect (with AWS and Snowflake)

As the Data Solutions Architect, you will be tasked with providing expert guidance and technical leadership in the design, development, and deployment of data products and data pipeline systems on AWS and Snowflake platforms. You will lead a dynamic team of data engineers and data scientists to build scalable, high-performance data solutions that deliver tangible business value, particularly for Raw Materials Data Products.

Key Responsibilities:

• Lead the architectural design and implementation of data products and data pipeline solutions on AWS, ensuring optimal scalability, security, and performance.
• Offer technical mentorship and guidance to the team, fostering an innovative and collaborative work culture.
• Collaborate with cross-functional teams, including product managers and business stakeholders, to align data solutions with business goals and requirements.
• Develop and maintain technical documentation and design specifications for the solutions.
• Drive the technical roadmap for data product development on AWS, adhering to industry standards and best practices.
• Oversee quality assurance processes, such as code reviews and testing, to ensure the robustness and reliability of data products.
• Communicate complex technical concepts clearly to non-technical stakeholders, ensuring alignment on the business impact of data solutions.

Qualifications:

• Demonstrated experience in technical leadership roles focused on building data products and pipeline solutions on AWS.
• Expertise in AWS services such as Lambda, Fargate, EC2, S3, AWS Glue, Athena, Step Functions, Event Bridge, and SQS, alongside Snowflake.
• Strong understanding of data architecture, data modeling, and ETL processes in the context of AWS and Snowflake solutions.
• Proficiency in SQL for data querying and manipulation.
• Strong problem-solving skills with the ability to troubleshoot and resolve data-related issues.
• Experience with Python development and DevOps tools such as GitLab CI/CD and AWS CDK.
• Knowledge of Snowflake tools, including WHs, dbt, and Vault.

Preferred skills:

• Experience with Liquibase.
• Ability to work with both structured and unstructured data sources.
• Proven ability to optimize and fine-tune data pipelines for enhanced performance and scalability.

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