1 to 25 of 162 Permanent dbt Jobs in London

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 ❯

Tech Stack: Cloud Data Warehouse - Snowflake AWS Data Solutions - Kinesis, SNS, SQS, S3, ECS, Lambda Data Governance & Quality - Collate & Monte Carlo Infrastructure as Code - Terraform Data Integration & Transformation - Python, DBT, Fivetran, Airflow CI/CD - Github Actions/Jenkins Business Intelligence - Looker Skills & Attributes We'd Like To See: Extensive experience in data engineering, including designing and maintaining robust data More ❯

deliver value-focused data solutions We'd love to talk to you if: You've got solid experience working with Python, SQL, Spar and data pipeline tools such as dbt or Airflow You're comfortable working across cloud platforms - especially AWS (Glue, Lambda, Athena), Azure (Data Factory, Synapse), or GCP (Dataflow, BigQuery, Cloud Composer) You have a good understanding of More ❯

practices around CI/CD, infrastructure-as-code, and modern data tooling Introduce and advocate for scalable, efficient data processes and platform enhancements Tech Environment: Python, SQL, Spark, Airflow, dbt, Snowflake, Postgres AWS (S3), Docker, Terraform Exposure to Apache Iceberg, streaming tools (Kafka, Kinesis), and ML pipelines is a bonus What We're Looking For: 5+ years in Data Engineering More ❯

data models. Experience with Interface/API data modelling. Experience with CI/CD GITHUB Actions (or similar) Knowledge of Snowflake/SQL Knowledge of Apache Airflow Knowledge of DBT Familiarity with Atlan for data catalog and metadata management Understanding of iceberg tables Who we are: Were a business with a global reach that empowers local teams, and we undertake 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 ❯

Key Responsibilities: Design and maintain scalable data pipelines across diverse sources including CMS, analytics, ad tech, and social platforms. Lead engineering efforts to automate workflows using tools like Airflow, dbt, and Spark. Build robust data models to support dashboards, A/B testing, and revenue analytics. Collaborate with cross-functional teams to deliver actionable insights and support strategic initiatives. Drive More ❯

Key Responsibilities: Design and maintain scalable data pipelines across diverse sources including CMS, analytics, ad tech, and social platforms. Lead engineering efforts to automate workflows using tools like Airflow, dbt, and Spark. Build robust data models to support dashboards, A/B testing, and revenue analytics. Collaborate with cross-functional teams to deliver actionable insights and support strategic initiatives. Drive More ❯

and architectures Integrate with APIs of 3rd party data sets to enable data pipelines and reporting use cases Build data systems and pipelines using SaaS systems like AWS and DBT Cloud Build solutions to various business objectives using your technical skills and your extensive understanding of the TTS data landscape Collaborate with the product engineering team and the data analytics More ❯

Our products are recognised by industry leaders like Gartner's Magic Quadrant, Forrester Wave and Frost Radar. Our tech stack: Superset and similar data visualisation tools. ETL tools: Airflow, DBT, Airbyte, Flink, etc. Data warehousing and storage solutions: ClickHouse, Trino, S3. AWS Cloud, Kubernetes, Helm. Relevant programming languages for data engineering tasks: SQL, Python, Java, etc. What you will be More ❯

data pipelines, and ETL processes Hands-on experience with cloud platforms (GCP, AWS, Azure) and their data-specific services Proficiency in Python, SQL, and data orchestration tools (e.g., Airflow, DBT) Experience with modern data warehouse technologies (BigQuery, Snowflake, Redshift, etc.) Strong understanding of data modeling, data governance, and data quality principles Excellent communication skills with the ability to translate complex More ❯

detail and care about the features they implement. What we need from you: At least 3 years of relevant data engineering experience Strong Python and SQL skills Experience with dbt Experience with AWS Experience working with a columnar database such as Redshift Strong Experience with ETL/ELT and the management of data pipelines Familiarity with snowplow Experience with Data More ❯

reliable data-focused backend services Have hands-on experience with cloud infrastructure (GCP/AWS/Azure), infrastructure-as-code (Terraform), containerisation (Docker/k8s) and data pipelines (SQL, dbt, Airbyte) Love automation, process improvement and finding ways to help others work efficiently Are comfortable working autonomously and taking responsibility for the delivery of large technical projects Are eager to More ❯

reliable data-focused backend services Have hands-on experience with cloud infrastructure (GCP/AWS/Azure), infrastructure-as-code (Terraform), containerisation (Docker/k8s) and data pipelines (SQL, dbt, Airbyte) Love automation, process improvement and finding ways to help others work efficiently Are comfortable working autonomously and taking responsibility for the delivery of large technical projects Are eager to More ❯

reliable data-focused backend services Have hands-on experience with cloud infrastructure (GCP/AWS/Azure), infrastructure-as-code (Terraform), containerisation (Docker/k8s) and data pipelines (SQL, dbt, Airbyte) Love automation, process improvement and finding ways to help others work efficiently Are comfortable working autonomously and taking responsibility for the delivery of large technical projects Are eager to More ❯

Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to build interpretable and explainable ML models (using techniques such as SHAP) Desire to quantify the level of fairness and More ❯

for a Data Engineer to join their London-based team. Key Responsibilities: Design and maintain scalable data pipelines across diverse sources. Automate and optimise workflows using tools like Airflow, dbt, and Spark. Support data modelling for analytics, dashboards, and A/B testing. Collaborate with cross-functional teams to deliver data-driven insights. Work with cloud platforms (GCP preferred) and More ❯

for a Data Engineer to join their London-based team. Key Responsibilities: Design and maintain scalable data pipelines across diverse sources. Automate and optimise workflows using tools like Airflow, dbt, and Spark. Support data modelling for analytics, dashboards, and A/B testing. Collaborate with cross-functional teams to deliver data-driven insights. Work with cloud platforms (GCP preferred) and More ❯

day a week in a central London office High-growth scale-up with a strong mission and serious funding Modern tech stack: Python, SQL, Snowflake, Apache Iceberg, AWS, Airflow, dbt, Spark Work cross-functionally with engineering, product, analytics, and data science leaders What You'll Be Doing Lead, mentor, and grow a high-impact team of data engineers Define and More ❯

and operating data pipelines, warehouses, and scalable data architectures. Deep hands-on experience with modern data stacks. Our tech includes Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, and Apache Spark, deployed via AWS, Docker, and Terraform. Experience with similar technologies is essential. Coaching & Growth Mindset: Passion for developing others through mentorship, feedback, and knowledge sharing. Pragmatic Problem 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 ❯

pipeline development Experience with IaC tools such as Terraform or Ansible for deployment and infrastructure management Hands-on experience with; ETL/ELT orchestration and pipeline tools (Airflow, Airbyte, DBT, etc.) Data warehousing tools and platforms (Snowflake, Iceberg, etc.) SQL databases, particularly MySQL Desired Experience: Experience with cloud-based services, particularly AWS Proven ability to manage stakeholders, their expectations and More ❯

and secure use of machine learning. Key Focus Areas Own and execute enterprise data strategy Build and lead a multi-disciplinary data & AI team Drive modern data platform development (dbt, Airflow, Snowflake, Looker/Power BI) Deliver business-critical analytics and reporting Support responsible AI/ML initiatives Define data governance, privacy, and compliance frameworks What We're Looking For More ❯

strong team player A quick learner, able to pick up new skills and technologies easily and enjoys working on complex issues Experienced in wealth management - beneficial Experience with Redshift, dbt, python and Google Looker - beneficial This role isn't for you if You rely on a lot of top-down direction. Here, you'll have a lot of freedom and More ❯

a fast-paced startup or agile environment. Strong background in schema design and dimensional data modeling. Able to communicate data architecture clearly with internal stakeholders. Experience with Azure, Airflow, DBT, Kubernetes, GitHub. Bonus points for: open-source contributions, an active GitHub profile, and curiosity for the latest in tech. A natural problem-solver who loves making things work. Focused on More ❯