1 to 25 of 71 Snowflake Schema Jobs in London

Build and optimize data pipelines using dbt, ensuring clean and accessible data. Monitor data quality and implement validation processes in collaboration with data engineers. Create scalable data models in Snowflake using dbt and identify opportunities for efficiency gains. Optimize workflows and monitor system performance for continuous improvements. Ensure data practices meet regulatory standards and assist in compliance reporting. Stay … Build and optimize data pipelines using dbt, ensuring clean and accessible data. Monitor data quality and implement validation processes in collaboration with data engineers. Create scalable data models in Snowflake using dbt and identify opportunities for efficiency gains. Optimize workflows and monitor system performance for continuous improvements. Ensure data practices meet regulatory standards and assist in compliance reporting. Stay … processors. Proven experience in SQL,DBT and Snowflake. Proficiency in building and managing data transformations with dbt, with experience in optimizing complex transformations and documentation. Hands-on experience with Snowflake as a primary data warehouse, including knowledge of performance optimization, data modeling, and query tuning. Strong proficiency in data analysis tools and languages (e.g., SQL, Python). Strong understanding More ❯

in building, maintaining, and scaling modern data pipelines and transformation workflows (ELT), ideally within a cloud or lakehouse environment. Strong experience with data modeling techniques (e.g. dimensional, star/snowflake schemas) and analytics layer design to support business intelligence and self-serve reporting. Proficiency in analytics engineering tools such as airflow, SQL, and version control systems like Git. Hands … data engineers, data scientists, and business stakeholders. Familiarity with cloud-based data ecosystems such as AWS, Azure, or GCP, and working with data warehouse/lakehouse technologies such as Snowflake, BigQuery, Redshift, or Athena/Glue. Essential: Proficient in writing clean, efficient, and maintainable SQL and Python code, particularly for data transformation and analytics use cases. Strong understanding of … data modeling concepts, including star/snowflake schemas and designing models optimized for reporting and dashboarding. Proficient in analytics tools such as Power BI, Plotly/Dash, or similar for building interactive and impactful visualizations. Deep experience with modern ELT workflows and transformation tools (e.g., dbt, custom SQL models, etc). Strong ability to debug and optimize slow or More ❯

in building, maintaining, and scaling modern data pipelines and transformation workflows (ELT), ideally within a cloud or lakehouse environment. Strong experience with data modeling techniques (e.g. dimensional, star/snowflake schemas) and analytics layer design to support business intelligence and self-serve reporting. Proficiency in analytics engineering tools such as airflow, SQL, and version control systems like Git. Hands … data engineers, data scientists, and business stakeholders. Familiarity with cloud-based data ecosystems such as AWS, Azure, or GCP, and working with data warehouse/lakehouse technologies such as Snowflake, BigQuery, Redshift, or Athena/Glue. Essential: Proficient in writing clean, efficient, and maintainable SQL and Python code, particularly for data transformation and analytics use cases. Strong understanding of … data modeling concepts, including star/snowflake schemas and designing models optimized for reporting and dashboarding. Proficient in analytics tools such as Power BI, Plotly/Dash, or similar for building interactive and impactful visualizations. Deep experience with modern ELT workflows and transformation tools (e.g., dbt, custom SQL models, etc). Strong ability to debug and optimize slow or More ❯

Build and optimise data pipelines using dbt, ensuring clean and accessible data. Monitor data quality and implement validation processes in collaboration with data engineers. Create scalable data models in Snowflake using dbt and identify opportunities for efficiency gains. Optimize workflows and monitor system performance for continuous improvements. Ensure data practices meet regulatory standards and assist in compliance reporting. Stay … DBT) Extensive experience in building and managing data transformations with dbt, with experience in optimising complex transformations and documentation. Hands-on experience with popular Cloud data-warehouses such as Snowflake or Redshift, including knowledge of performance optimisation, data modeling, and query tuning. Highly Proficient in data analysis tools and languages (e.g., SQL, Python). Strong understanding of data modeling More ❯

Professional Experience: 3–5 years in Data Engineering, Data Warehousing, or programming within a dynamic (software) project environment. Data Infrastructure and Engineering Foundations: Data Warehousing: Knowledge of tools like Snowflake, DataBricks, ClickHouse and traditional platforms like PostgreSQL or SQL Server. ETL/ELT Development: Expertise in building pipelines using tools like Apache Airflow, dbt, Dagster. Cloud providers: Proficiency in … Microsoft Azure or AWS. Programming and Scripting: Programming Languages: Strong skills in Python and SQL. Data Modeling and Query Optimization: Data Modeling: Designing star/snowflake schemas and understanding normalization and denormalization. SQL Expertise: Writing efficient queries and optimizing for performance. DevOps and CI/CD: Version Control: Using Git and platforms like GitHub, GitLab, or Bitbucket. Data Governance More ❯

non-technical audiences, tailoring communication style based on the audience. Data Modeling and Warehousing: •Design and implement data models optimized for analytical workloads, using dimensional modeling techniques (e.g., star schema, snowflake schema). •Participate in the design, implementation, and maintenance of data warehouses ensuring data integrity, performance, and scalability. BASIC QUALIFICATIONS •Educational Background: Bachelor's or Master … Skills: Working knowledge of R or Python for analytics, data manipulation, and algorithm development. •Data Warehousing Knowledge: In-depth knowledge of data warehousing principles, dimensional modeling techniques (e.g., star schema, snowflake schema), and data quality management. •Communication and Collaboration Abilities: Excellent verbal and written communication skills, with the ability to effectively communicate technical concepts; experience gathering requirements … R; experience with machine learning algorithms and techniques is a plus. •Experience in building and maintaining APIs for data integration and delivery. •Experience with data warehouse platforms such as Snowflake a plus. ABOUT GOLDMAN SACHS At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in More ❯

integrity, and security across processes. Document technical solutions and maintain best practices in data engineering. Your Profile: Proven experience in Python programming for data engineering. Hands-on expertise with Snowflake, including data modeling, performance tuning, and SQL scripting. Strong understanding of data warehousing concepts and cloud data platforms. Proficiency with version control systems like Git. Familiarity with CI/ More ❯

databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra) for efficient data storage and retrieval. Data Warehousing : Experience with data warehousing solutions, such as Amazon Redshift, Google BigQuery, Snowflake, or Azure Synapse Analytics, including data modelling and ETL processes. ETL Processes: Proficient in designing and implementing ETL (Extract, Transform, Load) processes using tools like Apache NiFi, Talend, or … Pipeline Orchestration : Experience with workflow orchestration tools such as Apache Airflow or Prefect to manage and schedule data pipelines. Data Modelling : Strong understanding of data modelling concepts (e.g., star schema, snowflake schema) and best practices for designing efficient and scalable data architectures. Data Quality and Governance : Knowledge of data quality principles and experience implementing data governance practices More ❯

Lambda, IAM, Terraform, GitHub, CI/CD) Proficiency in SQL and Python for data processing and automation Experience working with data modeling tools and practices (e.g., dimensional, star/snowflake schema, dbt) Solid understanding of data governance, metadata, and quality frameworks Strong collaboration and communication skills, with the ability to work cross-functionally in an Agile environment Desirable More ❯

Lambda, IAM, Terraform, GitHub, CI/CD) Proficiency in SQL and Python for data processing and automation Experience working with data modeling tools and practices (e.g., dimensional, star/snowflake schema, dbt) Solid understanding of data governance, metadata, and quality frameworks Strong collaboration and communication skills, with the ability to work cross-functionally in an Agile environment Exposure More ❯

and workflow automation Experience with AWS data tools (e.g. Redshift, Glue, Lambda, S3 ) and infrastructure tools such as Terraform Understanding of data modelling concepts (e.g. dimensional models, star/snowflake schemas) Knowledge of data quality, access controls , and compliance frameworks Nice to Have Experience with orchestration or pipeline frameworks like Airflow or dbt Familiarity with BI platforms (e.g. Power More ❯

Dash for data visualisation Strong experience with AWS or equivalent Spark or Kafka (experience with one or the other expected) Proficiency in data modelling techniques such as Star or Snowflake schema Experience designing and deploying transformation pipelines in production Passion for data quality , including implementing API checks and robust validation logic Exposure to automation scripting in Python to More ❯

of the Technical Customer Operations team. We are looking for a Data Engineer, specializing in data modeling, ETL processes, and cloud-based data solutions. This position requires expertise in Snowflake, Azure, and Power BI, with a strong focus on building semantic models and supporting analytics. Company Description We work with consumer goods companies to optimize their data sources, drive … collaborate closely with clients to achieve their desired results, covering Retail, Out of Home, E-Commerce, and Field Sales. Key Responsibilities: ETL Pipelines: Design and optimize ETL pipelines in Snowflake and Azure Data Factory to streamline data integration and transformation. Data Models: Build and manage semantic data models in Snowflake and Power BI to support scalable, user-friendly … analytics and reporting. Automation: Develop Snowflake stored procedures using Python to automate workflows and handle complex data transformations. Data Integrity: Ensure data integrity and accessibility within Snowflake to support effective data warehousing operations. Collaboration: Collaborate with analytics and business teams to align data models with reporting needs and business goals. Qualifications: This role is ideal for a self More ❯

We are looking for a Data Engineer, specializing in data modelling, ETL processes, and cloud-based data solutions. This position requires expertise in Snowflake, Azure, Python and Power BI, with a strong focus on building semantic models and supporting analytics. Please only apply if you are confident with the above. This is a Remote role with a few in … scalability. We collaborate closely with clients to achieve their desired results, covering Retail, Out of Home, E-Commerce, and Field Sales. Key Responsibilities: Design and optimize ETL pipelines in Snowflake and Azure Data Factory to streamline data integration and transformation. Build and manage semantic data models in Snowflake and Power BI to support scalable, user-friendly analytics and … reporting. Develop Snowflake stored procedures using Python to automate workflows and handle complex data transformations. Ensure data integrity and accessibility within Snowflake to support effective data warehousing operations. Collaborate with analytics and business teams to align data models with reporting needs and business goals. Qualifications: Strong experience in Data Engineering, with a focus on data modelling, ETL, and More ❯

play a key part in designing, building, and optimising scalable data pipelines, ensuring high-quality, actionable data is readily available to drive decision-making. Working with modern tools like Snowflake and dbt, you’ll build and maintain our data infrastructure and collaborate with cross-functional teams, including analysts and stakeholders, to support reporting and insights. You’ll also have … organisation. Key Responsibilities Design, develop, and maintain scalable and reliable ETL pipelines to extract, transform, and load data from a variety of sources. Build and optimise data models using Snowflake and dbt to ensure accuracy, integrity, and accessibility across the organisation. Write and optimise complex SQL queries for data transformation, reporting, and analysis. Collaborate with analysts and stakeholders to More ❯

comfortable with CLI tools. Strong analytical thinking, problem-solving and communication skills. Growth mindset, curiosity, and ability to quickly learn new services. Understanding of data warehousing concepts, star/snowflake schemas, and DAX. Basic knowledge of MLOps or prompt engineering for generative AI. Benefits Are you ready to join the Data & AI Apps team at Nasstar? • AI is in More ❯

data migration projects and cloud transformation Deep understanding of enterprise architecture frameworks and methodologies Experience with financial risk systems and analytics platforms Strong technical background in database platforms (Oracle, Snowflake) Understanding of cloud architecture principles (AWS preferred) Excellent communication and stakeholder management skills Ability to translate complex technical concepts for non-technical stakeholders PREFERRED CERTIFICATIONS Cloud platform certifications (AWS … DAMA) Project/Program Management certifications (PMP, Prince2, Agile/Scrum) AI/ML certifications or specialized training TECHNICAL SKILLS Enterprise systems architecture AWS and cloud technologies Oracle and Snowflake platforms Data modeling and design Data lineage and governance tools ETL/ELT processes Big data and analytics platforms Financial risk systems and methodologies Programming knowledge (Python, SQL, etc. … DevOps and CI/CD principles Knowledge graph and semantic web technologies Machine learning operations (MLOps) AI-focused data catalog tools Schema registry and metadata management systems Feature store architecture for machine learning PIMCO follows a total compensation approach when rewarding employees which includes a base salary and a discretionary bonus. Base salary is the fixed component of compensation More ❯

If you're looking to contribute, grow, and work on diverse data challenges, join us! Your Contribution Design and develop efficient and scalable data models and data marts (e.g.star schema, snowflake schema) using best practices for data warehousing and business intelligence that are optimized for self-service analytics tools Collaborate with business stakeholders (e.g. finance, marketing, operations More ❯

or Scala to support data transformation, orchestration, and integration tasks. Work with cloud platforms like AWS to deploy, monitor, and manage data services. Utilise tools such as DBT and Snowflake for data modeling, transformation, and warehouse management. Collaborate with analysts, data scientists, and business stakeholders to ensure data accuracy, consistency, and availability. Apply strong analytical thinking and problem-solving … on expertise in Spark, Kafka, and other distributed data processing frameworks. Solid programming skills in Python Strong familiarity with cloud data ecosystems, especially AWS. Strong knowledge of DBT and Snowflake Strong problem-solving mindset with the ability to diagnose and resolve technical challenges. Excellent communication skills and the ability to work effectively in a cross-functional team. More ❯

or Scala to support data transformation, orchestration, and integration tasks. Work with cloud platforms like AWS to deploy, monitor, and manage data services. Utilise tools such as DBT and Snowflake for data modeling, transformation, and warehouse management. Collaborate with analysts, data scientists, and business stakeholders to ensure data accuracy, consistency, and availability. Apply strong analytical thinking and problem-solving … on expertise in Spark, Kafka, and other distributed data processing frameworks. Solid programming skills in Python Strong familiarity with cloud data ecosystems, especially AWS. Strong knowledge of DBT and Snowflake Strong problem-solving mindset with the ability to diagnose and resolve technical challenges. Excellent communication skills and the ability to work effectively in a cross-functional team. More ❯

Solid experience in SQL/T-SQL for data extraction and transformation * Hands-on experience with Azure technologies (Data Lake, Data Factory, Synapse, etc.) * Data modelling experience (star/snowflake schemas, normalization, etc.) * Familiarity with ETL processes and working alongside Data Engineers * Excellent communication and stakeholder management skills * Insurance industry experience (ideally Reinsurance) Desirable Experience: * Exposure to Google Cloud More ❯

ETL processes, and cloud-based data solutions, with a particular focus on advanced SQL for data transformation and optimisation. The ideal candidate will have hands-on experience working with Snowflake, Azure Data Factory, and Power BI, with proven ability to design and maintain semantic data models that support scalable analytics. Experience working with consumer goods or retail data models More ❯

Knowledge of Data visualization tools. Additional qualifications, capabilities, and skills Experience with AWS services, Lambdas, Terraform. Knowledge of Java. Front-end development skills. User Experience design skills. Experience with Snowflake and Data modeling. Experience working in large-scale, global, highly regulated institutions. About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to More ❯

Job Description Role: Snowflake Data Architect Location: Hove, UK Type: Permanent Work Mode: Hybrid Role & Responsibilities Define and implement the end-to-end architecture of Data warehouse on Snowflake. Create and maintain conceptual, logical, and physical data models in Snowflake. Design data pipelines and ingestion frameworks using Snowflake tools. Collaborate with Data Governance teams to establish data lineage More ❯

Job Description Job Title: Snowflake Data Architect Job Location: Hove, UK/Hybrid Is it Permanent/Contract: Permanent Job Description Who we are? We are a leading global IT Services company, dedicated to driving digital transformation and innovation for businesses around the world. Founded in 1990, Client has grown into a global trusted partner for enterprises, offering comprehensive … and implement the end-end architecture of Data warehouse on Snowflake. Create and maintain conceptual, Logical and Physical Data Models in Snowflake. Design Data Pipelines and ingestion frameworks using Snowflake tools. Work with Data Governance teams to establish Data lineage, Data quality and access control mechanisms. Engage with Data stewards and other stake holders to build a comprehensive & scalable More ❯