What does a successful Data Engineering Architect do?
You will join the Data Solutions domain in EMEA. As a key contributor, you will be responsible for designing and implementing scalable data architecture solutions that empower our organization to make data-driven decisions. You will collaborate with cross-functional teams to create robust data pipelines and ensure data availability, reliability, and quality across the organization.
What you will do:
- Analyse system requirements and design, develop, and maintain enterprise data models that meet business requirements.
- Design and oversee the implementation of integration architectures, including data flow, process flow, and ETL integrations
- Build and optimize robust data pipelines for ingestion, processing, and storage of large datasets.
- Ensure data governance, security, and compliance best practices are followed throughout the data lifecycle.
- Evaluate and implement new data technologies and tools to enhance data processing and analytics capabilities.
- Monitor, troubleshoot, and optimize data workflows to ensure performance and reliability.
- Document data architecture, processes, and best practices to ensure knowledge sharing within the organization.
- Provide ongoing production support and maintenance, ensuring system observability and reliability to quickly identify and resolve issues.
What you will need to have:
- Minimum 7 years’ experience in a similar position within a dynamic and fast paced environment at enterprise production scale.
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
- Strong Proficiency in SQL and DBT with thorough understanding of data transformation processes
- Strong Experience in AWS (IAM, Lambda, EKS, S3 (Datalake), EMR (Pyspark), Datalakehouse (Iceberg), MWAA and other services relevant to data architecture and analytics
- Expertise in Snowflake, with a proven ability to optimize queries for efficient data retrieval.
- Experience with both batch and streaming data solutions.
- Familiarity with data modelling concepts (Inmon, Kimball, Data Vault, etc.).
What would be great to have:
- Exposure to CI/CD or Infrastructure-as-code (Terraform or any other) is a plus.
- Knowledge of data quality and security best practices is advantageous.
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