1 to 25 of 238 dbt Jobs in the UK excluding London

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 ❯

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 ❯

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 ❯

While in this position your duties may include but are not limited to: Support the design, development, and maintenance of scalable data pipelines using tools such as Apache Airflow, dbt, or Azure Data Factory. Learn how to ingest, transform, and load data from a variety of sources, including APIs, databases, and flat files. Assist in the setup and optimisation of More ❯

an Agile environment. Technical Proficiency: Deep technical expertise in software and data engineering, programming languages (python, java etc.). Understanding of orchestration (Composer, DAGs), data processing (Kafka, Flink, DataFlow, dbt), and database capabilities (e.g. BigQuery, CloudSQL, BigTable). Container technologies (Docker, Kubernetes), IaaC (Terraform) and experience with cloud platforms such as GCP. CI/CD: Detailed understanding of working automated More ❯

lakes or Lakehouse's Excellent communication skills with the ability to explain complex technical concepts clearly and persuasively Desirable Skills for the Senior Data Engineer: Experience with event sourcing, dbt, or related data transformation tools Familiarity with PostgreSQL and cloud-native data services (Azure Event Hub, Redshift, Kinesis, S3, Blob Storage, OneLake, or Microsoft Fabric) Understanding of machine learning model More ❯

Experience In-depth experience of applying data engineering techniques in current role. Experience using SQL and Python to effectively automate data pipelines and other tasks with tools such as dbt, airflow. Strong experience with data lakehouse architecture (e.g DataBricks,Redshift, Snowflake, BigQuery). Exposure to cloud services and their configuration (e.g AWS). Experience in building and documenting data architectures More ❯

Experience In-depth experience of applying data engineering techniques in current role. Experience using SQL and Python to effectively automate data pipelines and other tasks with tools such as dbt, airflow. Strong experience with data lakehouse architecture (e.g DataBricks,Redshift, Snowflake, BigQuery). Exposure to cloud services and their configuration (e.g AWS). Experience in building and documenting data architectures More ❯

modern data architectures (e.g. Databricks, Snowflake) Collaborating with multidisciplinary teams to deliver real business value What were looking for Strong experience with Python, SQL , and pipeline tools such as dbt or Airflow Proven background in data modelling, warehousing, and performance optimisation Hands-on experience with cloud data services (Glue, Lambda, Synapse, BigQuery, etc.) A consultancy mindset adaptable, collaborative, and delivery More ❯

data architectures (e.g. Databricks, Snowflake) Collaborating with multidisciplinary teams to deliver real business value What we re looking for Strong experience with Python, SQL , and pipeline tools such as dbt or Airflow Proven background in data modelling, warehousing, and performance optimisation Hands-on experience with cloud data services (Glue, Lambda, Synapse, BigQuery, etc.) A consultancy mindset adaptable, collaborative, and delivery More ❯

data architectures (e.g. Databricks, Snowflake) Collaborating with multidisciplinary teams to deliver real business value What we’re looking for Strong experience with Python, SQL , and pipeline tools such as dbt or Airflow Proven background in data modelling, warehousing, and performance optimisation Hands-on experience with cloud data services (Glue, Lambda, Synapse, BigQuery, etc.) A consultancy mindset – adaptable, collaborative, and delivery 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 ❯

Experience with version control (Git), testing, and code review practices Familiarity with cloud-based data environments (e.g. AWS, GCP, or Azure) Exposure to modern data tools such as Airflow, dbt, or Snowflake Experience or strong interest in streaming technologies like Apache Kafka Interest in MLOps and modern data engineering best practices Why join: You’ll be part of a company More ❯

Experience with version control (Git), testing, and code review practices Familiarity with cloud-based data environments (e.g. AWS, GCP, or Azure) Exposure to modern data tools such as Airflow, dbt, or Snowflake Experience or strong interest in streaming technologies like Apache Kafka Interest in MLOps and modern data engineering best practices Why join: You’ll be part of a company More ❯

Experience with cloud platforms (AWS, Azure, GCP) and tools like Snowflake, Databricks, or BigQuery . Familiarity with streaming technologies (Kafka, Spark Streaming, Flink) is a plus. Tools & Frameworks: Airflow, dbt, Prefect, CI/CD pipelines, Terraform. Mindset: Curious, data-obsessed, and driven to create meaningful business impact. Soft Skills: Excellent communication and collaboration — translating complex technical ideas into business insight 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 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 ❯

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 ❯

handle sensitive and confidential information Experience working with non-data stakeholders to translate their needs and generate useful results presented in an understandable way Familiarity with orchestration tools (Airflow, DBT) and data warehouse modelling Managing other data engineers Experience with customer and commercial datasets, especially in retail or FMCG A love of pets! About Jollyes Pets Jollyes are an award More ❯