1 to 25 of 91 Snowflake Jobs in Central 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 ❯

/CD pipelines for data solutions Solid experience with cloud platforms (e.g., AWS, Azure, or GCP), and their data services. Deep understanding of data warehousing concepts and technologies (e.g., Snowflake, Redshift). Strong knowledge of ETL/ELT processes and tools. Solid experience of utilising PowerBI or similar visualisation tools Experience working with big data technologies and frameworks (e.g., Spark 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 ❯

engineering teams delivering end-to-end data solutions across cloud and on-premise environments. Solution Architecture – Design modern data lakes, warehouses, and lakehouses using Databricks , with additional exposure to Snowflake, Azure Synapse, or Fabric being a bonus. Data Modelling – Build and optimise enterprise-grade data models across varied data layers. ETL/ELT Engineering – Use tooling such as Databricks, SSIS 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 communication skills. Desirable Certifications Bachelors degree in Data Science, Computer Science, Mathematics , or a related field. Microsoft Certified Azure Data Engineer Associate or Azure Database Administrator Associate . Snowflake Certified Data Engineer or equivalent certification in modern cloud data warehousing . Professional certifications in Python , SQL , or ETL/Data Pipelines (e.g., Coursera, DataCamp). Whats on Offer Salary 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 ❯

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 ❯

full potential of their data, reducing costs, mitigating risk, and uncovering new revenue opportunities through cutting-edge solutions and world-class talent. Working with major technology partners including Databricks, Snowflake, and Collibra, they deliver projects that revolutionise how data is used across sectors such as financial services, pharmaceuticals, energy, retail, healthcare, and manufacturing. The Role: Data Engineer (Databricks) We are More ❯

impact. You will: Architect, optimise, and deliver ELT pipelines and data workflows (using dbt, Airflow, SQL, Python). Own and evolve large-scale analytics platforms and data warehouse solutions (Snowflake, BigQuery, Redshift). Mentor engineers across analytics engineering and data engineering disciplines. Ensure data solutions meet best practices for governance, integrity, modelling, and scalability. Drive innovation in data orchestration, schema 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 ❯

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 complex enterprise environment. Strong proficiency in Advanced T-SQL and data warehouse modelling. Skilled in Python scripting. Hands-on experience with Azure Data Factory and Airflow. Familiarity with Snowflake is highly desirable. Strong problem-solving and analytical skills, with the ability to manage and interpret complex data sets. Excellent communication skills and the ability to work effectively with technical More ❯

Scala/Java) and SQL Deep experience with data pipeline orchestration tools (Airflow, dbt, Dagster, Prefect) Strong knowledge of cloud data platforms (AWS, GCP, or Azure) and data warehousing (Snowflake, BigQuery, Redshift) Hands-on experience with streaming technologies (Kafka, Kinesis, or similar) Solid understanding of data modelling, governance, and architecture best practices Familiarity with machine learning pipelines or AI model More ❯

you. The successful AWS Data Engineer candidate will have the chance to make a significant impact in designing the platform and working on cutting-edge technologies like Databricks and Snowflake in the heart of a leading global Investment Banks’ front-office. This is a rare greenfield role that offers the opportunity to solve the ultimate data pipeline challenge faced by More ❯

will: recognise opportunities to reuse existing data flows optimise the code to ensure processes perform optimally Tech Stack: Cloud: On AWS Infrastructure/Access Management: Using Terraform Data Platform: Snowflake Data Integration: Tool Fivetran Data Transformation Tool: DBT core Data Orchestration Tool: MWWA(Airflow managed by AWS) CI/CD Pipelines: Github Actions Program Languages: SQL, Python and Terraform For More ❯

ideally in Power BI . Software development methodologies (Sprints/Agile) and project management software (Jira Software). SQL Server Database Databricks (or Alternative Modern Data Platform such as Snowflake) Knowledge of Orchestration Tools and processes (e.g SSIS , ODI, Informatica, Data Factory) If you are interested in this Data Analyst role, please reply with your latest CV or send it More ❯

The successful Senior AWS Data Engineer candidate will have the chance to make a significant impact in designing the platform and working on cutting-edge technologies like Databricks and Snowflake in the heart of a leading global Investment Banks’ front-office. This is a rare greenfield role that offers the opportunity to solve the ultimate data pipeline challenge faced by More ❯

Data Engineer (Snowflake) – AI/Data Consulting Firm About Us We are an ambitious consulting firm focused on delivering cutting-edge solutions in data and AI. Our mission is to empower organisations to unlock the full potential of their data by leveraging platforms like Snowflake alongside other emerging technologies. As a Data Engineer, you will play a crucial role in … building and optimising data solutions, ensuring scalability, performance, and reliability for our clients’ complex data challenges. The Role As a Data Engineer (Snowflake) , you will be responsible for designing, implementing, and optimising large-scale data processing systems. You’ll work closely with clients, data scientists, and solution architects to build efficient data pipelines, reliable infrastructure, and scalable analytics capabilities. This … strong technical expertise, problem-solving ability, and the confidence to work in a dynamic, client-facing environment. Your Impact: Develop, implement, and optimise data pipelines and ELT processes on Snowflake . Work closely with clients to understand business requirements and translate them into technical solutions. Design and implement scalable, high-performance cloud data architectures. Ensure data integrity, quality, and security More ❯

building long-term client relationships is a must have. Relevant data or AI qualification (e.g. CDMC, DAMA, DCAM, ISACA ) Hands-on experience with data and AI platforms such as Snowflake, Databricks, Microsoft Purview, Collibra, Informatica, or AWS Experience with data analytics tools such as Alteryx, Tableau, Power BI, SQL , etc. Two stage interview process to start ASAP. More ❯

self-starter mindset with the ability to work independently and solve complex problems Experience working within a start-up environment Nice to have: Experience with modern data warehouses (e.g. Snowflake, BigQuery) Exposure to vector databases (e.g. Qdrant) Understanding of data needs for ML training Background or interest in cybersecurity , compiled languages (C/C Rust), or binary analysis 🌟 Why You More ❯

including strategy definition, vendor assessment, and governance adoption. Experience establishing reference data management and data quality practices at enterprise scale. Knowledge of analytical data architectures: data lakes, warehouses (e.g., Snowflake, BigQuery), BI/reporting, and ETL pipelines. Proficiency in public cloud platforms (AWS, Google Cloud Platform, Microsoft Azure). Experience with both transactional RDBMS and modern distributed/cloud-native More ❯

driven decisions that deliver measurable client and business outcomes. You’ll design, build, and maintain data pipelines, analytics models, and Power BI dashboards, integrating data from systems such as Snowflake, SQL databases, Bloomberg, and SimCorp. Sitting directly with the Investment Management team, you’ll work closely with both business and technology stakeholders, ensuring best practices in data governance, quality, and … automation. Key Responsibilities: Build and maintain ETL/ELT data pipelines in Snowflake, integrating internal and external data sources (Bloomberg, SimCorp, market data vendors). Develop Power BI dashboards and reports to support investment, risk, and operations teams. Create and optimise data models for analytics and decision-making. Ensure data accuracy, lineage, and governance across systems. Automate manual workflows to … enhance reporting efficiency. Collaborate with teams across Investment Management and Technology to deliver scalable, data-driven solutions. Skills & Experience: Strong Python and SQL skills; experience with Snowflake or other cloud data warehouses. Proven experience building dashboards and reports in Power BI (DAX, Power Query). Hands-on experience with ETL/ELT tools (dbt, Matillion, Informatica, etc.). Familiarity with More ❯