1 to 25 of 227 Permanent Snowflake Jobs in London

be great if you have: Experience of relevant cloud services within AWS, Azure or GCP. Experience working in an Agile environment. Experience working with common vendor products such as Snowflake or Data Bricks. Experience working with CI/CD tooling. What you'll get in return is: 25 days' annual leave, rising to 30 days with each year of service. More ❯

Job Title: Snowflake Centre of Excellence Lead Location: Central London (Hybrid - 2 to 3 days on site per week) Employment Type: Permanent Salary: up to £120,000 per annum + benefits About the Role: We are working with a prestigious client based in London who are seeking a Snowflake Lead to play a pivotal role in establishing and scaling their … Snowflake capability. This is a unique opportunity for a seasoned Snowflake professional to build a Centre of Excellence from the ground up within a fast-paced, high-impact environment. As the Snowflake CoE Lead, you will be instrumental in shaping the organisation's Snowflake strategy, architecture, and delivery model. You'll bring your deep technical expertise, leadership experience, and direct … engagement with Snowflake to build a best-in-class data platform offering. Key Responsibilities: Lead the design, setup, and growth of a Snowflake practice, including establishing a Centre of Excellence. Architect, implement, and maintain scalable data solutions using Snowflake. Collaborate closely with stakeholders across the organisation and with Snowflake directly to influence strategic direction. Mentor and lead a team of More ❯

DI, SAS Viya). An ability to write complex SQL queries. Project experience using one or more of the following technologies: Tableau, Python, Power BI, Cloud (Azure, AWS, GCP, Snowflake, Databricks). Project lifecycle experience, having played a leading role in the delivery of end-to-end projects, as 14, rue Pergolèse, Paris, Francewell as a familiarity with different development More ❯

HTTP/S REST APIs Experience with time-series databases (e.g., InfluxDB, kdb+, TimescaleDB) and real-time data processing. Familiarity with distributed computing and data warehousing technologies (e.g., Spark, Snowflake, Delta Lake). Strong understanding of data governance, master data management, and data quality frameworks. Solid grasp of web technologies and APIs (REST, JSON, XML, authentication protocols). Experience with More ❯

ML use cases. Qualifications: 5+ years of experience in analytics engineering, data engineering, or a related field. Advanced SQL skills and experience architecting solutions on modern data warehouses (e.g., Snowflake, BigQuery, Redshift). Hands-on experience with advanced modelling techniques in dbt. A deep understanding of ETL/ELT processes and tools (e.g., Fivetran, Airbyte, Stitch). Experience with data More ❯

like Tableau Big data – Hadoop eco-system, Distributions like Cloudera/Hortonworks, Pig and HIVE Data processing frameworks – Spark & Spark streaming Hands-on experience with multiple databases like PostgreSQL, Snowflake, Oracle, MS SQL Server, NOSQL (HBase/Cassandra, MongoDB) Experience in cloud data eco-system - AWS, Azure or GCP in the data engineering space with at least few complex & high More ❯

like Tableau Big data – Hadoop eco-system, Distributions like Cloudera/Hortonworks, Pig and HIVE Data processing frameworks – Spark & Spark streaming Hands-on experience with multiple databases like PostgreSQL, Snowflake, Oracle, MS SQL Server, NOSQL (HBase/Cassandra, MongoDB) Experience in cloud data eco-system - AWS, Azure or GCP in the data engineering space with at least few complex & high More ❯

with cloud platforms (GCP, AWS, Azure) and their data-specific services Proficiency in Python, SQL, and data orchestration tools (e.g., Airflow, DBT) Experience with modern data warehouse technologies (BigQuery, Snowflake, Redshift, etc.) Strong understanding of data modeling, data governance, and data quality principles Excellent communication skills with the ability to translate complex technical concepts for business stakeholders Strategic thinking with More ❯

orchestration tools and Agile/DevOps practices. Data Analytics Lead | Data Engineering Lead | Risk Reporting Lead | Risk Data Engineering | SQL Expert | Data Warehouse | Financial Risk Analytics | Risk Data Management | Snowflake | SQL Server | SSIS | Power BI | Regulatory Compliance | Market Risk | Credit Risk | Data Team Manager | Data Platform Lead | Data Transformation | Financial Institution | International Data Team | Data Platform Architecture Deerfoot Recruitment Solutions More ❯

orchestration tools and Agile/DevOps practices. Data Analytics Lead | Data Engineering Lead | Risk Reporting Lead | Risk Data Engineering | SQL Expert | Data Warehouse | Financial Risk Analytics | Risk Data Management | Snowflake | SQL Server | SSIS | Power BI | Regulatory Compliance | Market Risk | Credit Risk | Data Team Manager | Data Platform Lead | Data Transformation | Financial Institution | International Data Team | Data Platform Architecture Deerfoot Recruitment Solutions More ❯

formats (CSV, JSON, XML, Parquet) Experience with time-series databases (e.g., InfluxDB, kdb+, TimescaleDB) and real-time data processing. Familiarity with distributed computing and data warehousing technologies (e.g., Spark, Snowflake, Delta Lake). Strong understanding of data governance, master data management, and data quality frameworks. Excellent communication and stakeholder management skills. Ability to mentor junior engineers and foster a collaborative More ❯

making across the data and ML engineering domain on technical approaches to balance delivering near-term commercial impact and building long-term foundations. Our Tech Stack Cloud Data Warehouse - Snowflake AWS Data Solutions - Kinesis, SNS, SQS, S3, ECS, Lambda Data Governance & Quality - Collate & Monte Carlo Infrastructure as Code - Terraform Data Integration & Transformation - Python, DBT, Fivetran, Airflow CI/CD - Github More ❯

data platforms. SQL: Advanced proficiency in writing complex queries and optimizing performance. Python: Experience in data manipulation and scripting. Cloud Platforms: Hands-on experience with cloud data warehouses like Snowflake, Databricks, or BigQuery. OLAP, click stream, real time event processing databases. On prem data warehouse experience is valuable. Data Modeling: Expertise in designing and implementing data models for analytics. Data More ❯

skills in SQL and Python , with hands-on experience in relational databases across cloud and on-prem environments. Familiarity with modern data technologies such as Apache Spark , Kafka , or Snowflake . A comprehensive understanding of the data engineering lifecycle, including Agile delivery , DevOps , Git , APIs , containers , microservices , and pipeline orchestration . Nice to have: DP-203 Azure Data Engineering/ More ❯

skills in SQL and Python , with hands-on experience in relational databases across cloud and on-prem environments. Familiarity with modern data technologies such as Apache Spark , Kafka , or Snowflake . A comprehensive understanding of the data engineering lifecycle, including Agile delivery , DevOps , Git , APIs , containers , microservices , and pipeline orchestration . Nice to have: DP-203 Azure Data Engineering/ More ❯

/remote working and a salary between £50,000 and £70,000. As part of the data engineering team, youll design and deliver scalable data products using technologies like Snowflake, Power BI, Python, and SQL. Your work will enable self-service analytics and support data governance across the business. Key Responsibilities: Develop robust ETL/ELT pipelines and dimensional models More ❯

Engineer or in a similar data engineering/BI role Advanced SQL skills with hands-on experience using dbt for data modeling Strong familiarity with modern data platforms like Snowflake, Looker, AWS/GCP, Tableau, or Airflow Experience with version control tools (e.g., Git) Ability to design, build, and document scalable, reliable data models Comfortable gathering business requirements and translating More ❯

ideally within fintech or cloud-native organisations (AWS preferred). Strong technical background in data engineering, analytics, or data science. Experience with modern data stacks (e.g., SQL, dbt, Airflow, Snowflake, Looker/Power BI) and AI/ML tooling (e.g., Python, MLflow, MLOps). A track record of building and managing high-performing data teams. Strategic thinking and ability to More ❯

Modeling data for a civil service department replacing a legacy HR system Experience and qualifications Technical 3+ years' experience in data or software engineering Knowledge of Python, SQL, Databricks, Snowflake, and major cloud platforms (AWS/Azure/GCP) Ability to learn quickly and adapt to new technologies and sectors Understanding of data engineering best practices and system design Strong More ❯

meet compliance standards. Mentor: Upskill other platform engineers, data engineers and AI engineers to deliver and build adoption on your team's initiatives Our Tech Stack Cloud Data Warehouse - Snowflake AWS Data Solutions - Kinesis, SNS, SQS, S3, ECS, Lambda Data Governance & Quality - Collate & Monte Carlo Infrastructure as Code - Terraform Data Integration & Transformation - Python, DBT, Fivetran, Airflow CI/CD - Github More ❯

tools. Understanding of Agile methodologies. Additional Skills Experience mentoring or supporting team development. Knowledge of Azure SQL DB, Data Factory, Data Lake, Logic Apps, Data Bricks (Spark SQL), and Snowflake is advantageous. More ❯

Technical Skills: Proven expertise in designing, building, and operating data pipelines, warehouses, and scalable data architectures. Deep hands-on experience with modern data stacks. Our tech includes Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, and Apache Spark, deployed via AWS, Docker, and Terraform. Experience with similar technologies is essential. Coaching & Growth Mindset: Passion for developing others through More ❯

use of machine learning. Key Focus Areas Own and execute enterprise data strategy Build and lead a multi-disciplinary data & AI team Drive modern data platform development (dbt, Airflow, Snowflake, Looker/Power BI) Deliver business-critical analytics and reporting Support responsible AI/ML initiatives Define data governance, privacy, and compliance frameworks What We're Looking For Proven data More ❯

SQL. Vast experience in data modelling using tools such as Erwin, Power Designer, SQLDBM or Sparx EA. Minimum 10 years experience in using databases such as Oracle, SQL Server, Snowflake or any other OLTP and OLAP databases. Minimum 5 years experience with reporting tools: Power BI, Business Objects, Tableau or OBI. Understanding of Master Data Management technology landscape, processes and More ❯

as Terraform or Ansible for deployment and infrastructure management Hands-on experience with; ETL/ELT orchestration and pipeline tools (Airflow, Airbyte, DBT, etc.) Data warehousing tools and platforms (Snowflake, Iceberg, etc.) SQL databases, particularly MySQL Desired Experience: Experience with cloud-based services, particularly AWS Proven ability to manage stakeholders, their expectations and explain complex problems or solutions in a More ❯