1 to 25 of 113 Snowflake Jobs in the South East

Strong Data Engineer Language Skills (Python, SQL, Javascript) Experience of Azure, AWS or GCP cloud platforms and Data Lake/Warehousing Platforms such as Snowflake, Iceberg etc Experience of various ETL and Streaming Tools (Flink, Spark) Experience of a variety of data mining techniques (APIs, GraphQL, Website Scraping) Ability to More ❯

a positive and inclusive team culture What we’re looking for: Hands-on experience building and maintaining cloud-based data systems (e.g., Redshift, BigQuery, Snowflake) Strong coding skills in languages commonly used for data work (e.g., Python, Java, Scala) Deep understanding of ETL/ELT tools and workflow orchestration platforms More ❯

in data engineering (5+ years), with at least 2 in a people leadership role. Hands-on experience with data warehouse solutions such as Redshift, Snowflake, or BigQuery. Strong command of SQL and programming languages like Python, Scala, or Java. Familiarity with ETL/ELT tools (e.g., Airflow, Fivetran, dbt) and More ❯

Python, SQL, and modern ETL tools (e.g., Airflow, dbt) Solid grasp of cloud platforms (AWS/GCP/Azure) and data warehouses (e.g., BigQuery, Snowflake) Familiarity with streaming technologies (Kafka, Kinesis, etc.) Passion for clean, maintainable code and robust data systems Previous experience in a fintech or regulated environment is More ❯

Aladdin). Languages: Java, Python, or C# with Spring Boot or .NET Core. Integrations: Market data feeds (e.g., Refinitiv, Bloomberg). Data Platforms: Warehouses: Snowflake, Google BigQuery, or Amazon Redshift. Analytics: Tableau, Power BI, or Looker for client reporting. Big Data: Apache Spark or Hadoop for large-scale processing. AI More ❯

to AI infrastructure Building reliable, scalable, and flexible systems. Influence Opinion and decision-making across AI and ML Skills Python SQL/Pandas/Snowflake/Elasticsearch Docker/Kubernetes Airflow/Spark Familiarity with GenAI models/libraries Requirements 6+ years of relevant software engineering experience post-graduation A More ❯

tools (Terraform is a plus). Experience with Airflow or similar orchestration tools. Familiarity with MLflow or MLOps practices. Knowledge of data warehousing solutions (Snowflake, Redshift, BigQuery). Consulting background is a plus. Strong communication skills (oral & written) Rights to work in the UK is must (No Sponsorship available) Responsibilities More ❯

API Gateway, ECS) Experience designing and developing microservices with clean domain boundaries Good working knowledge of SQL and cloud databases (Aurora/Postgres, DynamoDB, Snowflake etc.) Familiarity with IaC tooling such as AWS CDK, CloudFormation or Terraform Experience working in Agile/Kanban teams with strong TDD principles CI/ More ❯

career. The difference you'll make: Designing, building, and maintaining our AWS Data Estate. This includes S3 lake formation, Iceburg and extends to our Snowflake platform. Designing AWS-based services and capabilities adopting appropriate modelling techniques following agreed architectures, design standards, patterns, and methodology. Leading AWS-based service design activities More ❯

stage. A very exciting opportunity! The following skills/experience is required: Strong Data Architect background Experience in Data Technologies to include: Finbourne LUSID, Snowflake, Hadoop, Spark. Experience in Cloud Platforms: AWS, Azure or GCP. Previously worked in Financial Services: Understanding of data requirements for equities, fixed income, private assets More ❯

Responsibilities : 16–18 years' experience in DWBI, Big Data, and Cloud Technologies. Hands-on expertise in at least 2 Cloud platforms (Azure, AWS, GCP, Snowflake, Databricks) and Big Data processing (e.g., Apache Spark, Beam). Proficiency in key technologies like BigQuery, Redshift, Synapse, Pub/Sub, Kinesis, Event Hubs, Kafka More ❯

architectures . Solid understanding of AWS services and DevOps principles. Passion for writing clean, maintainable code and improving team practices. Nice-to-Have Skills Snowflake/Data Warehousing DevOps & CI/CD experience GraphQL Benefits Competitive salary Pension & private medical (after probation) Employee discounts and more Ready to make an More ❯

or AWS Glue Cloud Native storage: Iceberg, RDS, RedShift, Kafka IaC: Terraform, Ansible CI/CD: Jenkins, Gitlab Other platforms such as Databricks or Snowflake will be considered You will have a fantastic opportunity to lead the Data Platform Engineering division whether you decide to take your career path in More ❯

this role. Knowledge of cloud-based database solutions (AWS, Azure, Google Cloud) is an advantage. Preferred Qualifications: Experience with big data technologies (Hadoop, Spark, Snowflake) is a plus. Certification in database technologies or testing methodologies. Knowledge of scripting languages like Python or Shell scripting for test automation. Work Environment: Hybrid More ❯

and trade data. Strong analytical and technical skills, particularly in: SQL (writing queries, data extraction and manipulation) Microsoft Excel (advanced) Power Apps Experience with Snowflake or similar cloud-based data warehouses Data modelling and architecture documentation Experience in Agile delivery methodologies (Scrum, Kanban). Familiarity with tools such as Azure More ❯

hands-on experience using SQL for multi-step/complex analytics is essential for this role. Experience in cloud platforms (GCP – BigQuery, Azure -Synapse, Snowflake) and exposure to data science tools/languages such as Python, dbt, D3, Github, GCP/AWS would be advantageous. (This is not a technical More ❯

years), preferably in the energy sector. Right to work in the UK. Strong proficiency in SQL and database technologies (e.g., MS SQL, Snowflake). Hands-on experience with ETL/ELT tools such as Azure Data Factory, DBT, AWS Glue, etc. Proficiency in Power BI and Advanced Analytics for insightful More ❯

Responsibilities Develop and optimize ETL/ELT processes to support data transformation and integrity for analytics. Explore and evaluate new data warehousing solutions, including Snowflake, to improve data accessibility and scalability. Partner with product and engineering teams to define data architecture and best practices for reporting. Ensure data security, compliance More ❯

Data Factory, Synapse, and Fabric ✅ Strong SQL & Python skills ✅ Experience across ETL/ELT, data lakes, modelling, and governance ✅ Exposure to Spark, Kafka, or Snowflake a plus ✅ Agile/DevOps mindset and experience with Git, APIs, microservices Bonus: DP-203 or Fabric Analytics certification highly desirable. Important: Must have the More ❯

.//Excellent programming skills in Python.//SQL/NoSQL database management systems (PostgresSQL, MongoDB).//Familiar with BigQuery, Snowflake, Firebolt and/or Amazon (preferred).//Ability to work on messy, complex real-world data challenges.//Knowledge of BI Tools More ❯

with ETL/ELT pipelines and database technologies like PostgreSQL and MongoDB Familiar with major cloud platforms and tools, ideally Amazon Web Services and Snowflake or BigQuery Solid understanding of data transformation, advanced analytics, and API-based data delivery Ability to work across departments with a collaborative, problem-solving mindset More ❯

backlog management, and stakeholder engagement Experience working with or managing Data Engineering teams, with the ability to translate technical and business needs Knowledge of Snowflake and AWS platforms Familiarity with ETL tools such as DBT and Matillion Understanding of SQL and Python—enough to contribute to technical discussions and guide More ❯

technologies. Skills and experience required: Minimum of 8+ years' experience in data engineering, with at least 3 years in a leadership capacity. Experience with Snowflake and Matillion preferred. Hands-on experience with large-scale real-time and batch data pipelines. Experience with Azure cloud platform, and security concepts i.e. Keyvault More ❯

in Python (NumPy, Pandas, Scikit-Learn, etc.), SQL, and cloud platforms such as GCP or AWS. Have experience working with modern databases like BigQuery, Snowflake, or Redshift. Have successfully deployed machine learning models or optimisation algorithms in production environments. Have a solid understanding of digital marketing and marketing analytics, including More ❯

building a robust data platform Great interpersonal skills and collaborative mindset Strong hands-on experience with modern cloud data warehouses such as Databricks/Snowflake, ideally on AWS Strong Python experience, including deep knowledge of the Python data ecosystem, with hands-on expertise in Spark and Airflow Hands-on experience More ❯