1 to 25 of 202 dbt Jobs in London

large datasets. Proven experience developing and maintaining production-level codebases . Experience with any public cloud provider (GCP, AWS, or Azure). Desirable Experience Experience with Kubeflow , Airflow , or dbt . Hands-on experience with Google Cloud Platform (GCP) . Knowledge of containerisation (Docker, Kubernetes) and CI/CD practices. Familiarity with data warehouse technologies (BigQuery, Redshift, Snowflake, etc.). More ❯

engineering the ingestion, storage, transformation and distribution of tick, timeseries, reference and alternative datasets. The technology stack spanson-premise and cloud infrastructure with technologies and tooling such as Python, dbt, KDB+, Snowflake, SQL, interfacing with Market Data vendors such as Bloomberg, Refinitiv, Factset and MorningStar. This is an exciting time for you to join the team they consolidate our technology More ❯

engineering the ingestion, storage, transformation and distribution of tick, timeseries, reference and alternative datasets. The technology stack spanson-premise and cloud infrastructure with technologies and tooling such as Python, dbt, KDB+, Snowflake, SQL, interfacing with Market Data vendors such as Bloomberg, Refinitiv, Factset and MorningStar. This is an exciting time for you to join the team they consolidate our technology More ❯

engineering the ingestion, storage, transformation and distribution of tick, timeseries, reference and alternative datasets. The technology stack spanson-premise and cloud infrastructure with technologies and tooling such as Python, dbt, KDB+, Snowflake, SQL, interfacing with Market Data vendors such as Bloomberg, Refinitiv, Factset and MorningStar. This is an exciting time for you to join the team they consolidate our technology More ❯

engineering the ingestion, storage, transformation and distribution of tick, timeseries, reference and alternative datasets. The technology stack spanson-premise and cloud infrastructure with technologies and tooling such as Python, dbt, KDB+, Snowflake, SQL, interfacing with Market Data vendors such as Bloomberg, Refinitiv, Factset and MorningStar. This is an exciting time for you to join the team they consolidate our technology More ❯

or GCP experience desirable). Solid understanding of data modelling and performance optimisation. Knowledge of data governance, compliance, and security frameworks. Desirable Skills: Familiarity with orchestration tools like Airflow, dbt, or Prefect . Experience with CI/CD and DevOps practices for data pipelines. Exposure to Power BI , Tableau , or other visualisation tools. Background in financial services or other regulated More ❯

full stack data development (from ingestion to visualization). Strong expertise in Snowflake, including data modeling, warehousing, and performance optimization. Hands-on experience with ETL tools (e.g., Apache Airflow, dbt, Fivetran) and integrating data from ERP systems like NetSuite. Proficiency in SQL, Python, and/or other scripting languages for data processing and automation. Familiarity with LLM integrations (e.g., for 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 ❯

/ELT processes and database fundamentals. A motivated, proactive mindset with a strong desire to learn and grow. Nice to Have: Exposure to data pipeline tools (e.g. Apache Airflow, dbt). Experience with containerisation tools like Docker. Familiarity with version control and CI/CD practices. Knowledge of BI tools (Looker, Tableau, or similar). If you’re excited to More ❯

/ELT processes and database fundamentals. A motivated, proactive mindset with a strong desire to learn and grow. Nice to Have: Exposure to data pipeline tools (e.g. Apache Airflow, dbt). Experience with containerisation tools like Docker. Familiarity with version control and CI/CD practices. Knowledge of BI tools (Looker, Tableau, or similar). If you’re excited to More ❯

/ELT processes and database fundamentals. A motivated, proactive mindset with a strong desire to learn and grow. Nice to Have: Exposure to data pipeline tools (e.g. Apache Airflow, dbt). Experience with containerisation tools like Docker. Familiarity with version control and CI/CD practices. Knowledge of BI tools (Looker, Tableau, or similar). If you’re excited to More ❯

/ELT processes and database fundamentals. A motivated, proactive mindset with a strong desire to learn and grow. Nice to Have: Exposure to data pipeline tools (e.g. Apache Airflow, dbt). Experience with containerisation tools like Docker. Familiarity with version control and CI/CD practices. Knowledge of BI tools (Looker, Tableau, or similar). If you’re excited to More ❯

Proven experience in a leadership or technical lead role, with official line management responsibility. Strong experience with modern data stack technologies, including Python, Snowflake, AWS (S3, EC2, Terraform), Airflow, dbt, Apache Spark, Apache Iceberg, and Postgres. Skilled in balancing technical excellence with business priorities in a fast-paced environment. Strong communication and stakeholder management skills, able to translate technical concepts More ❯

Proven track record building and maintaining scalable data platforms in production, enabling advanced users such as ML and analytics engineers. Hands-on experience with modern data stack tools - Airflow, DBT, Databricks, and data catalogue/observability solutions like Monte Carlo, Atlan, or DataHub. Solid understanding of cloud environments (AWS or GCP), including IAM, S3, ECS, RDS, or equivalent services. Experience More ❯

testing, CI/CD, automation). Proven track record of designing, building, and scaling data platforms in production environments. Hands-on experience with big data technologies such as Airflow, DBT, Databricks, and data catalogue/observability tools (e.g. Monte Carlo, Atlan, Datahub). Knowledge of cloud infrastructure (AWS or GCP) - including services such as S3, RDS, EMR, ECS, IAM. Experience More ❯

office once a week . Requirements: Proven experience as an Analytics 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 More ❯

data engineering type! Significant hands-on experience with AWS services focused on data flow, pipelines, data transformation, storage and streaming. Excellent data engineering skills, for example with SQL, Python, DBT and Airflow. Good understanding of service-oriented architecture; experience of exposing and consuming data via APIs, streams and webhooks. Experience designing scalable data models, warehouse/lakehouse architectures, and dimensional More ❯

data engineering type! Significant hands-on experience with AWS services focused on data flow, pipelines, data transformation, storage and streaming. Excellent data engineering skills, for example with SQL, Python, DBT and Airflow. Good understanding of service-oriented architecture; experience of exposing and consuming data via APIs, streams and webhooks. Experience designing scalable data models, warehouse/lakehouse architectures, and dimensional More ❯

data engineering type! Significant hands-on experience with AWS services focused on data flow, pipelines, data transformation, storage and streaming. Excellent data engineering skills, for example with SQL, Python, DBT and Airflow. Good understanding of service-oriented architecture; experience of exposing and consuming data via APIs, streams and webhooks. Experience designing scalable data models, warehouse/lakehouse architectures, and dimensional More ❯

data engineering type! Significant hands-on experience with AWS services focused on data flow, pipelines, data transformation, storage and streaming. Excellent data engineering skills, for example with SQL, Python, DBT and Airflow. Good understanding of service-oriented architecture; experience of exposing and consuming data via APIs, streams and webhooks. Experience designing scalable data models, warehouse/lakehouse architectures, and dimensional More ❯

and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a fast-paced environment. Preferred Qualifications Experience with Databricks or Ray. Familiarity with dbt and Airflow. Experience with data quality frameworks. Understanding of ML requirements and experience working with ML teams. Experience in robotics or a related field. Familiarity with cloud-based data storage More ❯

and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a fast-paced environment. Preferred Qualifications Experience with Databricks or Ray. Familiarity with dbt and Airflow. Experience with data quality frameworks. Understanding of ML requirements and experience working with ML teams. Experience in robotics or a related field. Familiarity with cloud-based data storage More ❯

and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a fast-paced environment. Preferred Qualifications Experience with Databricks or Ray. Familiarity with dbt and Airflow. Experience with data quality frameworks. Understanding of ML requirements and experience working with ML teams. Experience in robotics or a related field. Familiarity with cloud-based data storage More ❯

and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a fast-paced environment. Preferred Qualifications Experience with Databricks or Ray. Familiarity with dbt and Airflow. Experience with data quality frameworks. Understanding of ML requirements and experience working with ML teams. Experience in robotics or a related field. Familiarity with cloud-based data storage More ❯

SQL skills. Background in building and maintaining ETL/ELT pipelines in a cloud environment (AWS or Azure). Knowledge of data warehousing (e.g., Redshift, Postgres) and tools like DBT . Familiarity with CI/CD , data modelling, and Agile practices. Comfortable collaborating with Data Scientists and translating business needs into technical solutions. Experience leading or mentoring other engineers. Benefits More ❯