1 to 25 of 109 dbt Jobs in the UK

Remote (Mostly remote with some occasional travel to Hemel Hempstead) Contract: Outside IR35 Day rate: Up to £550 per day Duration: 6 months Start date: ASAP Key skills: Snowflake, DBT, SQL, Python, AWS and Kimball The Client who are in the process of migrating to SnowFlake therefore require extra support. As a result, they require someone from a strong SQL … Python development background with excellent working knowledge of Data Build Tool (DBT). You will be undertaking aspects of the development lifecycle and be experienced in data modeling, process design, development, and testing. And whilst this company is going through a large-scale migration, this will present you with an opportunity to be at the cutting edge of data engineering. … have experience in the following: - Advanced SQL knowledge - SnowFlake (ideally certified) - Python development - AWS cloud experience essential, relating to data tooling and development - Working knowledge of Data Build Tool (DBT). o Develop staging, intermediate and marts in DBT to achieve analytics requirements o Optimize existing models to make it more reusable by following DBT best practices o Spot opportunities More ❯

or changes. Build abstractions that make it easy to plug in new service behaviour or data models. Ensure emulators work seamlessly with orchestration and infrastructure-as-code tools (e.g., dbt, Terraform, Airflow, CDKs). Gather and act on feedback from internal and external teams to prioritize high-impact integrations. Build usage analytics and telemetry to understand adoption patterns and developer More ❯

teams. Hard Skills Required Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) essential; R (desirable) Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP Machine Learning & AI: Classification, regression, clustering, forecasting; NLP (text mining, sentiment, LLM fine-tuning); GenAI frameworks Analytics & Visualisation: BI tools (Power BI, Tableau, Looker), interactive More ❯

teams. Hard Skills Required Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) essential; R (desirable) Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP Machine Learning & AI: Classification, regression, clustering, forecasting; NLP (text mining, sentiment, LLM fine-tuning); GenAI frameworks Analytics & Visualisation: BI tools (Power BI, Tableau, Looker), interactive More ❯

Java is a plus) Cloud expertise ( AWS, Azure, or GCP ) Container orchestration skills ( Kubernetes, Docker ) Knowledge of streaming platforms ( Kafka, Spark, Flink ) Familiarity with pipeline/orchestration tools ( Airflow, dbt ) Experience with modern data warehouses ( Snowflake, BigQuery, Redshift ) Working knowledge of enterprise platforms ( Oracle DB, SAP IQ, SAP Data Services, SAP Business Objects ) and Power BI Experience with integration patterns More ❯

meaningful outcomes. Technical expertise: Advanced Python skills for data engineering tasks. Experience building and maintaining web scraping pipelines. Strong SQL skills, with expertise in performance tuning. Strong proficiency with dbt for data transformations. Hands-on experience with Apache Airflow or Prefect. Proficiency with GitHub, GitHub Actions, and CI/CD pipelines. Nice to have: Experience with GCP (BigQuery, Dataflow, Composer More ❯

and scientists working across Africa, Europe, the UK and the US. ABOUT THE ROLE Sand Technologies focuses on cutting-edge cloud-based data projects, leveraging tools such as Databricks, DBT, Docker, Python, SQL, and PySpark to name a few. We work across a variety of data architectures such as Data Mesh, lakehouse, data vault and data warehouses. Our data engineers More ❯

Python: schema design, transformations, query optimisation, automation, testing. Track record of buildingETL/ELT pipelines into modern warehouses (BigQuery, Snowflake, Redshift). Familiar with tools like Dagster, Airflow, Prefect, dbt, Dataform, SQLMesh. Cloud experience (we're on GCP) + containerisation (Docker, Kubernetes). Strong sense of ownership over data standards, security, and roadmap. A collaborator at heart - working with analysts More ❯

expertise with AWS services, including Glue, Redshift, Data Catalog, and large-scale data storage solutions such as data lakes. Proficiency in ETL/ELT tools (e.g. Apache Spark, Airflow, dbt). Skilled in data processing languages such as Python, Java, and SQL. Strong knowledge of data warehousing, data lakes, and data lakehouse architectures. Excellent analytical and problem-solving skills with More ❯

of the AWS services like Redshift, Lambda,S3,Step Functions, Batch, Cloud formation, Lake Formation, Code Build, CI/CD, GitHub, IAM, SQS, SNS, Aurora DB - Good experience with DBT, Apache Iceberg, Docker, Microsoft BI stack (nice to have) - Experience in data warehouse design (Kimball and lake house, medallion and data vault) is a definite preference as is knowledge of More ❯

modelling techniques (star schema, data vault, dimensional modelling). Proficiency in Excel-based data workflows for various Agile Retail projects. Hands-on experience with data pipeline orchestration tools (Airflow, dbt, Prefect, or similar). Benefits: Unlimited holiday Annual Wellbeing Allowance Flexible work culture Monthly socials and events Complimentary snack bar Employer pension contribution If you're a data enthusiast ready More ❯

modelling techniques (star schema, data vault, dimensional modelling). Proficiency in Excel-based data workflows for various Agile Retail projects. Hands-on experience with data pipeline orchestration tools (Airflow, dbt, Prefect, or similar). Benefits: Unlimited holiday Annual Wellbeing Allowance Flexible work culture Monthly socials and events Complimentary snack bar Employer pension contribution If you're a data enthusiast ready More ❯

engineering disciplines : Cloud Engineering Data Engineering (not building pipelines but designing and building the framework) DevOps MLOps/LLMOps Often work with the following technologies : Azure, AWS, GCP Airflow, dbt, Databricks, Snowflake, etc. GitHub, Azure DevOps and related developer tooling and CI/CD platforms, Terraform or other Infra-as-Code MLflow, AzureML or similar for MLOps; LangSmith, Langfuse and More ❯

Alerting: Prometheus, Datadog, Pagerduty Telemetry Standards: OpenTelemetry Application & Data Ecosystem (Supporting): Application Languages/Frameworks: Python, FastAPI, Flask, Node.js, React Data Streaming: Apache Kafka Data Processing/Transformation: Pandas, DBT Workflow Orchestration: Apache Airflow, Ray Machine Learning Stack: Serving: Triton Inference Server MLOps/Experiment Tracking: Weights and Biases, DVC Libraries/Frameworks: Transformers, HuggingFace Model Optimization/Formats: Onnx More ❯

Stack Cloud: Azure, sometimes GCP & AWS Data Platform: Databricks, Snowflake, BigQuery Data Engineering tools: Pyspark, Polars, DuckDB, Malloy, SQL Infrastructure-as-code: Terraform, Pulumi Data Management and Orchestration: Airflow, dbt Databases and Data Warehouses: SQL Server, PostgreSQL, MongoDB, Qdrant, Pinecone GenAI: OpenAI APIs, HuggingFace, LangChain, Talk-to-data Monitoring: Datadog About You We are looking for someone who can wear More ❯

use LLM frameworks : LangChain, LlamaIndex (or similar) Cloud & Dev : Azure/AWS/GCP, Docker, REST APIs, GitHub Actions/CI Data & MLOps : BigQuery/Snowflake, MLflow/DVC, dbt/Airflow (nice to have) Front ends (for internal tools) : Streamlit/Gradio/basic React Must-have experience 7+ years in Data Science/ML, including hands-on delivery More ❯

Strong proficiency in SQL, Python, and data modeling for analytical and operational use cases Hands-on experience with production-grade ETL/ELT frameworks and workflow orchestration (e.g., Airflow, dbt, Talend, AWS Glue, GCP Dataform/Cloud Composer) Proven ability to design, deploy, and optimize data warehouses and lakehouse architectures using technologies like BigQuery, Redshift, Snowflake, and Databricks Experience with More ❯

and enhancing data governance, this is your chance to play a vital role in a collaborative, fast-paced environment. What Youll Do: Design, build, and maintain efficient ETL pipelinesleveraging DBT or your tool of choiceto feed a BigQuery data warehouse. Transform raw data into clean, structured formats suitable for analysis. Collaborate across engineering and analytics teams to implement scalable data More ❯

databases such as PostgreSQL, DynamoDB, or OpenSearch. -Problem-Solver: Comfortable working in Linux environments and confident debugging logs, scripts, and production issues. -Additional Skills: Exposure to Kafka, Spark, or dbt Core, with an interest in domain-driven data contracts. Meet Citywire We cover - and connect - all sides of the $100 trillion global asset management industry - through our news, events and More ❯

team members to deliver outcome Highly motivated, with strong problem-solving skills and business acumen Desirable Skills Experience with data visualization tools (e.g., Looker, Tableau, Power BI) Familiarity with dbt, Airflow, or other modern data tools Exposure to marketing or e-commerce industries Additional Information Publicis Groupe operates a hybrid working pattern with full time employees being office-based three More ❯

goals Desirable Skills Background in e-commerce, marketing, or operations analytics Experience with data visualization tools (e.g., Looker, Tableau, Power BI) Familiarity with modern data stack tools such as dbt, Airflow, and Git-based workflows Experience contributing to data product development, working closely with engineers and product managers Additional Information Publicis Groupe operates a hybrid working pattern with full time More ❯

Data Platform Engineer, you will support the design, implementation, and management of a decentralised data architecture based on Data Mesh principles. You will work with technologies such as Snowflake, dbt, Microsoft Azure, and Microsoft Fabric to build scalable, secure, and high-performing platform capabilities. Your work will empower domain teams to autonomously own, access, and manage their data via self More ❯

in data engineering, warehousing, or platform leadership. Proven track record of delivering large-scale data warehouse migrations (BigQuery experience strongly preferred). Hands-on expertise with SQL, Python, Airflow, DBT/Dataform, Terraform , and modern data architecture. Strong leadership and stakeholder management skills. Experience driving complex data projects in agile, cross-functional teams. Nice-to-haves: Background in insurance or More ❯

Apache Superset. Maintain custom Python tooling around it. Integrate SSO with Azure AD via AWS AD Connector Build and operate data pipelines. Python grabbers on EKS. Logging, monitoring, alerts. dbt models. CI with GitHub Actions Administer Aurora PostgreSQL. Scale clusters. Optimize SQL. Add partitioning with pg_partman Ship web analytics. Export data from Superset or PostgreSQL to static JSON. Render More ❯

track record of building and managing talent pipelines in competitive markets. Technical Understanding Solid grasp of modern tech stacks including Python, React.js, cloud platforms (AWS, Azure), and data tools (dbt, Airflow, Snowflake) from a recruitment perspective. Ability to assess technical skills through structured interviews and practical assessments. Understanding of software development practices, agile methodologies, and DevOps culture. Familiarity with AI More ❯