1 to 25 of 63 Permanent dbt Jobs in the City of London

xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt) Track record turning research code into production services (CI/CD, containers etc) Strong SQL and data-management skills; experience querying large analytical databases (Snowflake highly desirable, but Redshift/ More ❯

with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). Desirable: Background in fintech or payments. Knowledge of streaming frameworks (Kafka, Kinesis). Experience with dbt and data quality frameworks (e.g., Great Expectations ). What’s on Offer Competitive base salary + bonus Flexible hybrid working model (Liverpool Street office) Private healthcare & wellness benefits Learning and More ❯

Collaborate with engineers to integrate data best practices across teams Champion data quality, governance, and documentation Key Requirements: Strong experience with 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 More ❯

AWS or Azure or GCP) with IAC( Terraform )and CI/CD ( Jenkins ). Experience in developing and deploying AI/ML pipelines . Familiarity with Airflow , Redshift , and dbt . What you will do: Architect, build, and optimise robust ETL processes for efficient data extraction, transformation, and loading. Develop an automation model and sophisticated data pipelines using Python, Airflow More ❯

platforms (AWS, GCP, Azure) and cloud-based database services (Snowflake). Knowledge of data warehousing, orchestration and pipeline technologies (Apache Airflow/Kafka, Azure DataFactory etc.). Experience with DBT for modelling Server administration and networking fundamentals More ❯

in the businesses data arm. Requirements: 3+ Years data engineering experience Snowflake experience Proficiency across an AWS tech stack DevOps experience building and deploying using Terraform Nice to Have: DBT Data Modelling Data Vault Apache Airflow Benefits: Up to 10% Bonus Up to 14% Pensions Contribution 29 Days Annual Leave + Bank Holidays Free Company Shares Interviews ongoing don't More ❯

Python, and AWS tools (Redshift, Glue, S3, Lambda, etc.) Strong grasp of data modeling, governance, and pipeline orchestration Excellent communication and collaboration skills in Agile teams Desirable: Experience with dbt, Airflow, Monte Carlo, and BI tools (Power BI, Tableau, QuickSight) Knowledge of data product principles, real-time pipelines, and data enablement programs Join to shape a data-driven future and More ❯

ETL, data warehouses) Familiarity with Git, Docker, CI/CD pipelines, testing and monitoring Clear communicator, comfortable with cross-functional teams Desirable Experience APIs from major financial data providers dbt, Snowflake Kafka, Airflow Java feedhandler support Migration of legacy systems (e.g. MATLAB) This position offers a competitive compensation package and hybrid working model. More ❯

alternative datasets. The technology stack is similarly varied including a range of legacy and modern systems, across on-premises and cloud infrastructure with technologies and tooling such as Python, dbt, KDB+, Snowflake, SQL and 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 … Hedge Fund, Trading Firm, and/or working with Quant Trading Technology Expertise in Python and SQL and familiarity with relational and time-series databases. Exposure to Airflow and dbt, as well as Snowflake, Databricks or other Cloud Data Warehouses preferred. Experience implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps: Git, Docker, Jenkins More ❯

their data engineering practice this year. They are now on the look out for an experienced Senior Data Engineer to join the team, bringing technical expertise in Snowflake, AWS, DBT, and Terraform. Salary and Benefits Competitive salary of up to £100k Up to 10% Bonus Up to 14% Pensions Contribution Hybrid working from London office (2 in office, 3 from … include product-based work as well as migration tasks Due to your seniority you will also be tasked with mentoring junior engineers Work extensively and proficiently with Snowflake, AWS, DBT, Terraform, Airflow, SQL, and Python. Requirements: 3+ Years data engineering experience Snowflake experience Proficiency across an AWS tech stack DBT expertise Terraform experience Expert SQL and Python Data Modelling Data More ❯

alternative datasets. The technology stack is similarly varied including a range of legacy and modern systems, across on-premises and cloud infrastructure with technologies and tooling such as Python, dbt, KDB+, Snowflake, SQL and 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 … years experience gained in a Hedge Fund, Investment Bank, FinTech or similar Expertise in Python and SQL and familiarity with relational and time-series databases. Exposure to Airflow and dbt, as well as Snowflake, Databricks or other Cloud Data Warehouses preferred. Experience implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps: Git, Docker, Jenkins More ❯

There are opportunities for professional development, such as training programs, certifications, and career advancement paths. KEY RESPONSIBILITIES Design, develop, and maintain scalable data pipelines SQL, Azure ADF, Azure Functions, DBT Collaborate with analysts and stakeholders to understand their data needs, scoping and implementing solutions Optimising and cleaning of data warehouse, cleaning existing codebase and creating documentation. Monitor and troubleshoot data More ❯

quality rules, set up monitoring/logging, and support architecture decisions What You Bring Strong SQL & Python (PySpark); hands-on with GCP or AWS Experience with modern ETL tools (dbt, Airflow, Fivetran) BI experience (Looker, Power BI, Metabase); Git and basic CI/CD exposure Background in a quantitative field; AI/ML interest a plus Bonus: Experience in manufacturing More ❯

architects, product teams, analysts, and data scientists to implement data solutions that power analytics and reporting. The ideal candidate will have strong experience in data engineering, cloud platforms like DBT, Azure/AWS, data modeling, and ETL/ELT processes. You’ll be part of a dynamic and innovative team, working on cutting-edge technologies to deliver impactful data products … and enforce data governance and quality processes, ensuring accurate and consistent data flows across all systems. Cloud & Infrastructure Support: Work with cloud platforms such as AWS/Azure and DBT with Snowflake to build and maintain scalable data solutions. Continuous Improvement: Proactively look for ways to improve data systems, processes, and tools, ensuring efficiency and scalability. Key skills/knowledge …/experience: ETL/ELT & Data Pipelines: Solid understanding of ETL/ELT processes, along with hands-on experience building and maintaining data pipelines using DBT, Snowflake, Python, SQL, Terraform and Airflow Experience in designing and implementing data products and solutions on cloud-based architectures. Cloud Platforms: Experience working with cloud data warehouses and analytics platforms, such as Snowflake, and More ❯

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 data visualisation. Strong programming skills in Python for data processing, scripting, and automation. Familiarity with DBT, Airbyte, or More ❯

timely, and actionable for operational and ML-driven use cases About you: Strong background in software and data engineering leadership Proficient in Python, SQL, and modern ELT practices (e.g. dbt, Fivetran, Airflow) Deep knowledge of data warehousing (Snowflake), AWS services (e.g. Lambda, Kinesis, S3), and IaC (Terraform) Experienced in building data platforms with a focus on governance, reliability, and business More ❯

Professional Data Engineer certification Exposure to Agentic AI systems or intelligent/autonomous data workflows Experience with BI tools such as Looker Exposure to Databricks, Snowflake, AWS, Azure or DBT Academic background in Computer Science, Mathematics or a related field This is an opportunity to work in a forward-thinking environment with access to cutting-edge projects, ongoing learning, and More ❯

with cloud platforms such as AWS (e.g., S3, Redshift, Lambda) , Azure (e.g., Data Factory, Synapse) , or GCP (e.g., BigQuery, Cloud Functions) . Familiarity with data orchestration tools (e.g., Airflow, dbt) and version control (Git). Solid understanding of data governance, security, and compliance frameworks . Nice to Have: Experience with data lake architectures (Delta Lake, Lakehouse). Familiarity with BI More ❯

coaching, leading and management skills, able to upskill a small team and help them transition to more technical work. Strong technical skills in Python, SQL and tools such as dbt, Snowflake, AWS S3, KDB and SQL Server. Solid understanding of financial instruments such as Equities, Futures, Forwards, CDS, IRS and ETFs with deep knowledge in at least one asset class. More ❯

FS) Deep expertise in the full data engineering lifecycle—from data ingestion through to end-user consumption Practical experience with modern data tools and platforms, including Redshift, Airflow, Python, DBT, MongoDB, AWS, Looker, and Docker Strong grasp of best practices in data modelling, transformation, and orchestration Proven ability to build and support both internal analytics solutions and external-facing data More ❯

understanding of data in relation to dynamic pricing, revenue operations & management, demand forecasting, competitor analysis etc. would be useful! SQL, Python, Cloud (GCP, Azure, AWS or Snowflake), Airflow/dbt etc. Interested in hearing more? Apply More ❯

in Python or Scala to support data transformation, orchestration, and integration tasks. Work with cloud platforms like AWS to deploy, monitor, and manage data services. Utilise tools such as DBT and Snowflake for data modeling, transformation, and warehouse management. Collaborate with analysts, data scientists, and business stakeholders to ensure data accuracy, consistency, and availability. Apply strong analytical thinking and problem … engineer Hands-on expertise in Spark, Kafka, and other distributed data processing frameworks. Solid programming skills in Python Strong familiarity with cloud data ecosystems, especially AWS. Strong knowledge of DBT and Snowflake Strong problem-solving mindset with the ability to diagnose and resolve technical challenges. Excellent communication skills and the ability to work effectively in a cross-functional team. More ❯

enterprise data warehouses (Snowflake, BigQuery), lakes, and CDPs. Understanding of data pipelines, contracts, lineage, APIs, and data governance frameworks. Comfortable navigating GDPR, CCPA and other compliance requirements. Familiar with dbt, Airflow, and cloud platforms (AWS, GCP, Azure). Proven ability to manage backlogs, engage stakeholders and deliver in Agile environments. Analytical mindset with a strong commercial awareness. Why Apply? Excellent More ❯

platform teams in a production environment Proven success with modern data infrastructure: distributed systems, batch and streaming pipelines Hands-on knowledge of tools such as Apache Spark, Kafka, Databricks, DBT or similar Familiarity with data warehousing, ETL/ELT processes, and analytics engineering Programming proficiency in Python, Scala or Java Experience operating in a cloud-native environment (e.g. AWS, GCP More ❯

platform teams in a production environment Proven success with modern data infrastructure: distributed systems, batch and streaming pipelines Hands-on knowledge of tools such as Apache Spark, Kafka, Databricks, DBT or similar Familiarity with data warehousing, ETL/ELT processes, and analytics engineering Programming proficiency in Python, Scala or Java Experience operating in a cloud-native environment (e.g. AWS, GCP More ❯