Data Architect (City of London)

Location: London

Contract Type: Contract

Working Model: Hybrid

Overview:

We are seeking an experienced Data Architect to join our growing data team and lead the design and implementation of scalable, secure, and high-performance data solutions. You’ll play a key role in architecting modern data platforms using Snowflake , SQL , Python , and leading cloud technologies to support advanced analytics, reporting, and machine learning initiatives across the business.

Key Responsibilities:

• Design and maintain end-to-end data architectures, data models, and pipelines in Snowflake and cloud platforms (AWS, Azure, or GCP).
• Develop and optimize scalable ELT/ETL processes using SQL and Python.
• Define data governance, metadata management, and security best practices.
• Collaborate with data engineers, analysts, product managers, and stakeholders to understand data needs and translate them into robust architectural solutions.
• Oversee data quality, lineage, and observability initiatives.
• Recommend and implement performance tuning for large-scale data sets.
• Ensure platform scalability, cost-efficiency, and system reliability.

Required Skills & Experience:

• Proven experience as a Data Architect or Senior Data Engineer working on cloud-native data platforms.
• Strong hands-on experience with Snowflake – data modeling, performance tuning, security configuration, and data sharing.
• Proficiency in SQL for complex querying, optimization, and stored procedures.
• Strong coding skills in Python for data transformation, scripting, and automation.
• Experience with cloud platforms such as AWS (e.g., S3, Redshift, Lambda) , Azure (e.g., Data Factory, Synapse) , or GCP (e.g., BigQuery, Cloud Functions) .
• Familiarity with data orchestration tools (e.g., Airflow, dbt) and version control (Git).
• Solid understanding of data governance, security, and compliance frameworks .

Nice to Have:

• Experience with data lake architectures (Delta Lake, Lakehouse).
• Familiarity with BI/visualization tools (Tableau, Power BI, Looker).
• Knowledge of streaming data tools (Kafka, Kinesis).
• Background in supporting ML/AI pipelines or data science environments.