Data Engineering

Summary: The Data Engineering role requires extensive experience in data and analytics, particularly with AWS data platforms and Snowflake architecture. The position involves engaging with client stakeholders, presenting solutions, and developing intellectual property and frameworks. Candidates must possess strong communication skills and hands-on experience with various data technologies and methodologies.

Key Responsibilities:

• Engage with principal data architects of client stakeholders.
• Conduct regular client presentations and presales discussions.
• Develop strategies and IP/solution assets, accelerators, and frameworks.
• Work independently with customers to deliver solutions.
• Collaborate with AWS and Snowflake partners.

Key Skills:

• 13-18 years of overall Data and Analytics experience.
• Minimum 10+ years in AWS data platform including AWS S3, AWS Glue, AWS Redshift, AWS Athena, AWS Sagemaker, AWS Quicksight, and AWS MLOPS.
• Snowflake DWH architecture, Snowflake Data Sharing, Snowpipe, Polaris catalog, and data governance.
• Knowledge of Python, Streamlit, Matillion, DBT, Atlan, Terraform, Kubernetes, Data Vault, Data Mesh.
• Excellent presentation and communication skills.
• Hands-on experience with AWS Cloud Data Platforms and at least 2 AWS certifications.
• Expertise in Snowflake including DWH, ETL, security, and metadata aspects.
• Experience with open-source software platforms and languages (e.g., Java, Python, Scala).
• Understanding of AWS Bedrock, AI services, and Snowflake Cortex services implementation lifecycle.
• Strong written, verbal, and presentation communication skills.

Salary (Rate): undetermined

City: London

Country: UK

Working Arrangements: undetermined

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT