1 to 25 of 168 Permanent Snowflake Jobs in the City of London

4+ years of experience across data engineering, cloud computing, or data warehousing Minimum 2 years in hands-on development capacity Expertise in one or more modern cloud data platforms: Snowflake, Databricks, AWS Redshift, Microsoft Fabric, or similar Understanding of data modelling principles, dimensional modelling, and database design Proficiency in SQL and query optimization Comprehensive knowledge of ETL/ELT processes More ❯

4+ years of experience across data engineering, cloud computing, or data warehousing Minimum 2 years in hands-on development capacity Expertise in one or more modern cloud data platforms: Snowflake, Databricks, AWS Redshift, Microsoft Fabric, or similar Understanding of data modelling principles, dimensional modelling, and database design Proficiency in SQL and query optimization Comprehensive knowledge of ETL/ELT processes More ❯

Snowflake Data Engineer Location: Central London office space by Mansion House/Cannon Street/Monument (EC4V) Transform lives through data and AI Who we are: We deliver powerful data and AI solutions that minimise operational costs, strengthen resilience against risk, and uncover revenue opportunities. Clients can retain expert teams to drive lasting adoption while futureproofing their workforce with exceptional … including financial services, insurance, asset management, pharmaceuticals, energy and natural resources, retail, healthcare, manufacturing, and mobility. As a preferred partner of today’s leading technology providers - such as Databricks, Snowflake and Collibra - delivery is accelerated and revolutionary solutions are co-created. The lives of consultants, clients, and their customers are transformed through data and AI. The Role: We are seeking … a Snowflake Data Engineer to lead the design, development and deployment of cloud data platforms and analytics solutions using Snowflake. This combines hands-on engineering, solution architecture and technical leadership. You will translate business requirements into scalable Snowflake solutions, guide project teams on best practices for data modelling and ELT design, and ensure that outcomes deliver measurable value for our More ❯

Snowflake Data Engineer Location: Central London office space by Mansion House/Cannon Street/Monument (EC4V) Transform lives through data and AI Who we are: We deliver powerful data and AI solutions that minimise operational costs, strengthen resilience against risk, and uncover revenue opportunities. Clients can retain expert teams to drive lasting adoption while futureproofing their workforce with exceptional … including financial services, insurance, asset management, pharmaceuticals, energy and natural resources, retail, healthcare, manufacturing, and mobility. As a preferred partner of today’s leading technology providers - such as Databricks, Snowflake and Collibra - delivery is accelerated and revolutionary solutions are co-created. The lives of consultants, clients, and their customers are transformed through data and AI. The Role: We are seeking … a Snowflake Data Engineer to lead the design, development and deployment of cloud data platforms and analytics solutions using Snowflake. This combines hands-on engineering, solution architecture and technical leadership. You will translate business requirements into scalable Snowflake solutions, guide project teams on best practices for data modelling and ELT design, and ensure that outcomes deliver measurable value for our More ❯

and ability to work with both technical and non-technical stakeholders. Nice to Have: • Experience in energy or financial trading environments. • Familiarity with cloud-based data platforms (e.g. Databricks, Snowflake). • Knowledge of data governance, lineage, and metadata management. • Exposure to data cataloguing tools and data quality frameworks. More ❯

and ability to work with both technical and non-technical stakeholders. Nice to Have: • Experience in energy or financial trading environments. • Familiarity with cloud-based data platforms (e.g. Databricks, Snowflake). • Knowledge of data governance, lineage, and metadata management. • Exposure to data cataloguing tools and data quality frameworks. More ❯

level and translating requirements into solution blueprints, proposals, and presentations. Enterprise Solution Design – Architect end-to-end data and cloud solutions across platforms such as Azure, AWS, GCP, Databricks, Snowflake, Synapse, or Azure Fabric. Cloud Strategy & Adoption – Define and lead cloud migration, modernisation, and optimisation strategies using tools such as Terraform, Azure DevOps, and CI/CD pipelines. Data Products More ❯

flows through everything they build. What You’ll Do Build and own data pipelines that connect product, analytics, and operations Design scalable architectures using tools like dbt , Airflow , and Snowflake/BigQuery Work with engineers and product teams to make data easily accessible and actionable Help evolve their data warehouse and ensure high data quality and reliability Experiment with automation More ❯

flows through everything they build. What You’ll Do Build and own data pipelines that connect product, analytics, and operations Design scalable architectures using tools like dbt , Airflow , and Snowflake/BigQuery Work with engineers and product teams to make data easily accessible and actionable Help evolve their data warehouse and ensure high data quality and reliability Experiment with automation More ❯

version control (Git), testing, and code review practices Familiarity with cloud-based data environments (e.g. AWS, GCP, or Azure) Exposure to modern data tools such as Airflow, dbt, or Snowflake Experience or strong interest in streaming technologies like Apache Kafka Interest in MLOps and modern data engineering best practices Why join: You’ll be part of a company with a More ❯

and SQL . Hands-on experience with data orchestration tools (Airflow, dbt, Dagster, or Prefect). Solid understanding of cloud data platforms (AWS, GCP, or Azure) and data warehousing (Snowflake, BigQuery, Redshift). Experience with streaming technologies (Kafka, Kinesis, or similar). Strong knowledge of data modelling, governance, and architecture best practices . Excellent leadership, communication, and stakeholder management skills. More ❯

and SQL . Hands-on experience with data orchestration tools (Airflow, dbt, Dagster, or Prefect). Solid understanding of cloud data platforms (AWS, GCP, or Azure) and data warehousing (Snowflake, BigQuery, Redshift). Experience with streaming technologies (Kafka, Kinesis, or similar). Strong knowledge of data modelling, governance, and architecture best practices . Excellent leadership, communication, and stakeholder management skills. More ❯

maintaining data pipelines in production environments Strong Python and SQL skills (Pandas, PySpark, query optimisation) Cloud experience (AWS preferred) including S3, Redshift, Glue, Lambda Familiarity with data warehousing (Redshift, Snowflake, BigQuery) Experience with workflow orchestration tools (Airflow, Dagster, Prefect) Understanding of distributed systems, batch and streaming data (Kafka, Kinesis) Knowledge of IaC (Terraform, CloudFormation) and containerisation (Docker, Kubernetes) Nice to More ❯

maintaining data pipelines in production environments Strong Python and SQL skills (Pandas, PySpark, query optimisation) Cloud experience (AWS preferred) including S3, Redshift, Glue, Lambda Familiarity with data warehousing (Redshift, Snowflake, BigQuery) Experience with workflow orchestration tools (Airflow, Dagster, Prefect) Understanding of distributed systems, batch and streaming data (Kafka, Kinesis) Knowledge of IaC (Terraform, CloudFormation) and containerisation (Docker, Kubernetes) Nice to More ❯

Architect and optimize data pipelines and workflows using modern tools (e.g., dbt, Airflow, SQL, Python). Take ownership of large-scale analytics platforms and data warehouse solutions (such as Snowflake, BigQuery, Redshift). Mentor and guide engineers across analytics and data engineering disciplines. Ensure solutions adhere to best practices for data governance, integrity, and scalability. Drive continuous innovation in data More ❯

Architect and optimize data pipelines and workflows using modern tools (e.g., dbt, Airflow, SQL, Python). Take ownership of large-scale analytics platforms and data warehouse solutions (such as Snowflake, BigQuery, Redshift). Mentor and guide engineers across analytics and data engineering disciplines. Ensure solutions adhere to best practices for data governance, integrity, and scalability. Drive continuous innovation in data More ❯

Data Engineer, particularly in data modelling. Strong SQL and hands-on dbt experience. Ability to convert business requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. More ❯

Data Engineer, particularly in data modelling. Strong SQL and hands-on dbt experience. Ability to convert business requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. More ❯

frameworks. Metadata & Lineage Management — Design metadata models, lineage tracking, and glossaries; implement automated enrichment, sensitive data detection, and trust indicators. Integration & Automation — Build and maintain connectors across platforms like Snowflake, Databricks, Tableau, Power BI, and Salesforce . Implement REST APIs and event-driven automation for near real-time metadata synchronization. Data Governance Enablement — Define RBAC, data ownership models, workflows, and More ❯

frameworks. Metadata & Lineage Management — Design metadata models, lineage tracking, and glossaries; implement automated enrichment, sensitive data detection, and trust indicators. Integration & Automation — Build and maintain connectors across platforms like Snowflake, Databricks, Tableau, Power BI, and Salesforce. Implement REST APIs and event-driven automation for near real-time metadata synchronization. Data Governance Enablement — Define RBAC, data ownership models, workflows, and certification More ❯

a simple manner. Technical Skills: Advanced SQL skills essential. Experience with visualisation tools, such as Metabase, Tableau, Looker and PowerBi. Knowledge of dbt. Familiarity with data warehouses like BigQuery, Snowflake and Redshift. Knowledge in another programming language such as Python or R or a keen desire to develop programming skills. Good statistical understanding. Other Skills: Strong ability and desire to More ❯

a simple manner. Technical Skills: Advanced SQL skills essential. Experience with visualisation tools, such as Metabase, Tableau, Looker and PowerBi. Knowledge of dbt. Familiarity with data warehouses like BigQuery, Snowflake and Redshift. Knowledge in another programming language such as Python or R or a keen desire to develop programming skills. Good statistical understanding. Other Skills: Strong ability and desire to More ❯

ELT, and data pipeline design. Hands-on experience with data lakehouse, warehouse, and streaming data architectures. Working knowledge of SQL, Python, and relevant data engineering frameworks (e.g. Databricks, Synapse, Snowflake, Redshift). Experience designing data platforms leveraging PaaS and SaaS solutions. Solid understanding of information governance, metadata management, and master data management principles. Experience leading data design across full project More ❯

ELT, and data pipeline design. Hands-on experience with data lakehouse, warehouse, and streaming data architectures. Working knowledge of SQL, Python, and relevant data engineering frameworks (e.g. Databricks, Synapse, Snowflake, Redshift). Experience designing data platforms leveraging PaaS and SaaS solutions. Solid understanding of information governance, metadata management, and master data management principles. Experience leading data design across full project More ❯

pipelines Automating and orchestrating workflows (AWS Glue, Azure Data Factory, GCP Dataflow) Working across leading cloud platforms (AWS, Azure, or GCP) Implementing and optimising modern data architectures (e.g. Databricks, Snowflake) Collaborating with multidisciplinary teams to deliver real business value What we’re looking for Strong experience with Python, SQL , and pipeline tools such as dbt or Airflow Proven background in More ❯