51 to 75 of 390 Snowflake Jobs in the UK

SSIS, Talend or Pentaho • Data governance and data management tools such as Informatica MDM, Informatica AXON, Informatica EDC, and Collibra • MySQL, SQL Server, Oracle, Snowflake, PostgreSQL and NoSQL databases • Programming languages such as Spark or Python • Amazon Web Services, Microsoft Azure or Google Cloud and distributed processing technologies such as more »

Salary: £60,000 - £70,000 + 12.5% Bonus Key areas: SQL Data Engineer, Azure Data Engineer, Azure Data Factory, Azure Databricks, Azure Data Services, Snowflake, SQL Server, Data, BI, BI Development, MS BI Chapman Tate is collaborating with a leading Housing Association that is revolutionizing the industry through innovative data more »

design, implement and manage data lake/data warehouse platforms. (Some of the following types of providers: AWS, Microsoft Azure, Google Cloud Platform, Databricks, Snowflake, Cloudera, Spark, MongoDB) Done this at companies using high volumes of data, ideally in retailing. Other sectors where used high volume data would also be more »

predictive modelling, segmentation, time series analysis and applying these for decision making. You've had experience using cloud based analytical platforms such as Databricks, Snowflake, Google BigQuery and the like. You've a track record of taking data science products from conception through to deployment in production. You've had more »

have access to accurate up to date data We have a modern data stack already in place comprising of a Snowplow data pipeline, a Snowflake data warehouse, dbt as the data transformation tool and our BI tool, Looker. We don’t expect you to be fluent with all these technologies more »

Code Repository Management (e.g. GitHub, Subversion, Bitbucket) Has a CI/CD mindset for release purposes Desirable: Proven experience with Oracle ODI Familiarity with Snowflake Experience with collaboration tools i.e., Atlassian products (Jira, Confluence) Understanding of machine learning or data science Experience working on the cloud, preferably with AWS Practical more »

Spark experience Must have strong AWS experience Must have Terraform experience SQL & NoSQL experience Have built out Data Warehouses & built Data Pipelines Strong Databricks & Snowflake experience Docker, ECS, Kubernetes & Orchestration tools like Airflow or Step Functions are nice to have Contracts are running for 6 months initially, paying up to more »

a new Data Platform Act as Principle Data Expert to build out standards and mentor junior analysts Drive Data Engineering Solutions Key Skills Matillion Snowflake SQL Expert in building data pipelines ETL Strong Modelling and Data warehousing background Financial Services/experience of working in a regulated environment Benefits more »

data pipelines and data architecture Desired Skills: Experience with Python. Familiarity with AWS and Data Platforms Knowledge of Enterprise SaaS development, data lakes like snowflake This is a role that would be great for a Software Engineer that wants to drive the architecture for a product that has the potential more »

a team of Data Engineers previously. Experience with Cloud Technologies (AWS or GCP preferred). Strong proficiency with Python/SQL. Big Query or Snowflake experience, ideally exposure to DBT. HOW TO APPLY Please register your interest by sending your CV to luke.frost@xcede.com via the Apply Link. more »

requirement Experience required: As a Senior Data Engineer you will be required to demonstrate most of the below opportunities from prior/current experience. Snowflake database. dbt. Python development. Version control. Integration and deployment pipelines (CI/CD, DataOps). SQL Server, Oracle database. SSIS, SSRS, Power BI. Advanced SQL more »

required Expertise with Core Java, namely multithreading, accompanied with some Python is also acceptable Advanced SQL. Experience with cloud technologies is a plus (AWS, Snowflake, etc) Familiarity with equities and equity derivatives within a real-time electronic trading environment is required Strong communication skills; ability to liaise with investment professionals more »

definition of Big Data architecture with different tools and environments: Cloud (AWS, Azure and GCP), Cloudera, No-sql databases (Cassandra, Mongo DB), ELK, Kafka, Snowflake, etc. Past experience in Data Engineering and data quality tools (Informatica, Talend, etc.) Previous involvement in working in a Multilanguage and multicultural environment Proactive, tech more »

environment ☁️ 🔹 Proven ability to design, implement, and utilize various database structures with a focus on cloud-based data services such as Azure, Databricks, and Snowflake ❄️ 🔹 Experience in building ETL/ELT data pipelines and applying DevOps (CI/CD) concepts to test, schedule, and deploy to a production environment 🔄 If more »

their investment models. Tech is also completely flexible. Most of the work is done within Python, C# and Scala with a range of databases. Snowflake is widely used, as are Docker and Kubernetes for containerisation. ETL and ELT tech are also used every day, primarily Airflow, Spark, Hive and a more »

build their investment models.Tech is also completely flexible. Most of the work is done within Python, C# and Scala with a range of databases. Snowflake is widely used, as are Docker and Kubernetes for containerisation. ETL and ELT tech are also used every day, primarily Airflow, Spark, Hive and a more »

equivalent analyst position Proficiency in PL/SQL and an additional object-oriented programming language Experience in big data instances such as Cloudera, Azure, Snowflake, etc. Structured thinking with the ability to break down ambiguous problems and propose impactful data modeling designs Ability to roll out analytics dashboards (e.g., Power more »

knowledge of database structure systems, data mining, data analysis, and strong software engineering skills. Strong understanding of Data Engineering Proficiency in AWS, data warehousing (Snowflake, Databricks, Redshift), big data frameworks (Spark, Kafka), container orchestration platforms (Kubernetes), and data integration/ETL tools. Strong written and verbal communication skills, with the more »

Advanced knowledge of data visualization tools and dashboard design experience essential (Tableau preferred) Experience in the use of large databases and data warehouses required (Snowflake preferred) Experience with transitioning and deploying data science and quantitative models to Production environment required along with exposure to Agile development process -- ability to articulate more »

data quality, scalability, security, and ethics. SC Clearance/Eligibility required. Qualifications Experience in developing and deploying AI solutions using Python, TensorFlow, PyTorch, Keras, Snowflake, or similar frameworks and tools Knowledge of machine learning, deep learning, natural language processing, computer vision, or other AI techniques and algorithms Familiarity using cloud more »

data quality, scalability, security, and ethics. SC Clearance/Eligibility required. Qualifications Experience in developing and deploying AI solutions using Python, TensorFlow, PyTorch, Keras, Snowflake, or similar frameworks and tools Knowledge of machine learning, deep learning, natural language processing, computer vision, or other AI techniques and algorithms Familiarity using cloud more »

data quality, scalability, security, and ethics. SC Clearance/Eligibility required. Qualifications Experience in developing and deploying AI solutions using Python, TensorFlow, PyTorch, Keras, Snowflake, or similar frameworks and tools Knowledge of machine learning, deep learning, natural language processing, computer vision, or other AI techniques and algorithms Familiarity using cloud more »

data quality, scalability, security, and ethics. SC Clearance/Eligibility required. Qualifications Experience in developing and deploying AI solutions using Python, TensorFlow, PyTorch, Keras, Snowflake, or similar frameworks and tools Knowledge of machine learning, deep learning, natural language processing, computer vision, or other AI techniques and algorithms Familiarity using cloud more »

data quality, scalability, security, and ethics. SC Clearance/Eligibility required. Qualifications Experience in developing and deploying AI solutions using Python, TensorFlow, PyTorch, Keras, Snowflake, or similar frameworks and tools Knowledge of machine learning, deep learning, natural language processing, computer vision, or other AI techniques and algorithms Familiarity using cloud more »

technologies and tracking the technology innovations applicable to the solutions. Proven experience of working effectively with senior business stakeholders Experience of using tools including Snowflake, DBT, ADF and Azure Synapse Ability to lead teams and projects towards a common architecture approach and language. Strong communication and collaboration skills. Additional Information more »