ability (Vue, React or Angular good but not necessary) Agile The following is DESIRABLE, not essential: AWS or GCP Buy-side Data tools such as Glue, Athena, Airflow, Ignite, DBT, Arrow, Iceberg, Dremio Fixed Income performance, risk or attribution TypeScript and Node Role: Python Developer (Software Engineer Programmer Developer Python Fixed Income JavaScript Node Fixed Income Credit Rates Bonds ABS … to be in the office 1-2 times a week. The tech environment is very new and will soon likely include exposure to the following: Glue, Athena, Airflow, Ignite, DBT, Arrow, Iceberg, Dremio This is an environment that has been described as the only corporate environment with a start-up/fintech attitude towards technology. Hours are 9-5. 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 ❯
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 ❯
experience building production data pipelines Advanced Python skills (NumPy, Pandas, SQL Alchemy) and expert-level SQL across multiple database platforms Hands-on experience with modern data stack tools including dbt, Airflow, and cloud data warehouses (Snowflake, BigQuery, Redshift) Strong understanding of data modelling, schema design, and building maintainable ELT/ETL pipelines Experience with cloud platforms (AWS, Azure, GCP) and 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 dataMore ❯
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 ❯
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 ❯
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 ❯
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 ❯
of experience in data engineering or a related field, with a focus on building scalable data systems and platforms. Expertise in modern data tools and frameworks such as Spark, dbt, Airflow, Kafka, Databricks, and cloud-native services (AWS, GCP, or Azure) Understanding of data modeling, distributed systems, ETL/ELT pipelines, and streaming architectures Proficiency in SQL and at least More ❯
Bristol, Gloucestershire, United Kingdom Hybrid / WFH Options
Lloyds Bank plc
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 ❯
. Proficiency with Docker, Linux, and bash. Ability to document code, architectures, and experiments. Preferred Qualifications Experience with databases and data warehousing (Hive, Iceberg). Data transformation skills (SQL, DBT). Experience with orchestration platforms (Airflow, Argo). Knowledge of data catalogs, metadata management, vector databases, relational/object databases. Experience with Kubernetes. Understanding of computational geometry (meshes, boundary representations More ❯
love to talk to you if: You've led technical delivery of data engineering projects in a consultancy or client-facing environment You're experienced with Python, SQL, .NET, dbt, Airflow and cloud-native data tools (AWS, GCP or Azure) You have strong knowledge of data architecture patterns - including Lakehouse and modern warehouse design (e.g. Snowflake, BigQuery, Databricks) You know More ❯
Manchester, Lancashire, United Kingdom Hybrid / WFH Options
Dept Holding B.V
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 ❯
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 DataMore ❯
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 ❯
They are also proficient in Azure Event Hub and Streaming Analytics, Managed Streaming for Apache Kafka, Azure DataBricks with Spark, and other open source technologies like Apache Airflow and dbt, Spark/Python, or Spark/Scala. Required technical and professional expertise Commercial experience as a Data Engineer or similar role, with a strong emphasis on Azure technologies. Proficiency in 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 ❯
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 ❯
Manchester, Lancashire, United Kingdom Hybrid / WFH Options
Starling Bank Limited
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 ❯
Cardiff, South Glamorgan, United Kingdom Hybrid / WFH Options
Starling Bank Limited
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 ❯
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 ❯
