Data Architect / BI Architect

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.