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 ❯
london (city of london), south east england, united kingdom
Winston Fox
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 ❯
meaningful outcomes. Technical expertise: Advanced Python skills for data engineering tasks. Experience building and maintaining web scraping pipelines. Strong SQL skills, with expertise in performance tuning. Strong proficiency with dbt for data transformations. Hands-on experience with Apache Airflow or Prefect. Proficiency with GitHub, GitHub Actions, and CI/CD pipelines. Nice to have: Experience with GCP (BigQuery, Dataflow, Composer More ❯
Proficient in analytics tools such as Power BI, Plotly/Dash, or similar for building interactive and impactful visualizations. Deep experience with modern ELT workflows and transformation tools (e.g., dbt, custom SQL models, etc). Strong ability to debug and optimize slow or failing data pipelines and queries Familiarity with distributed systems (e.g., Spark, Kafka) and how they support scalable More ❯
City of London, London, United Kingdom Hybrid / WFH Options
OTA Recruitment
Proficient in analytics tools such as Power BI, Plotly/Dash, or similar for building interactive and impactful visualizations. Deep experience with modern ELT workflows and transformation tools (e.g., dbt, custom SQL models, etc). Strong ability to debug and optimize slow or failing data pipelines and queries Familiarity with distributed systems (e.g., Spark, Kafka) and how they support scalable More ❯
london, south east england, united kingdom Hybrid / WFH Options
OTA Recruitment
Proficient in analytics tools such as Power BI, Plotly/Dash, or similar for building interactive and impactful visualizations. Deep experience with modern ELT workflows and transformation tools (e.g., dbt, custom SQL models, etc). Strong ability to debug and optimize slow or failing data pipelines and queries Familiarity with distributed systems (e.g., Spark, Kafka) and how they support scalable More ❯
slough, south east england, united kingdom Hybrid / WFH Options
OTA Recruitment
Proficient in analytics tools such as Power BI, Plotly/Dash, or similar for building interactive and impactful visualizations. Deep experience with modern ELT workflows and transformation tools (e.g., dbt, custom SQL models, etc). Strong ability to debug and optimize slow or failing data pipelines and queries Familiarity with distributed systems (e.g., Spark, Kafka) and how they support scalable More ❯
london (city of london), south east england, united kingdom Hybrid / WFH Options
OTA Recruitment
Proficient in analytics tools such as Power BI, Plotly/Dash, or similar for building interactive and impactful visualizations. Deep experience with modern ELT workflows and transformation tools (e.g., dbt, custom SQL models, etc). Strong ability to debug and optimize slow or failing data pipelines and queries Familiarity with distributed systems (e.g., Spark, Kafka) and how they support scalable 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 ❯
field ● Proficiency in writing SQL queries and knowledge of cloud-based databases like Snowflake, Redshift, BigQuery or other big data solutions ● Experience in data modelling and tools such as dbt, ETL processes, and data warehousing ● Experience with at least one of the programming languages like Python, C++[2] , Java ● Experience with version control and code review tools such as Git More ❯
field ● Proficiency in writing SQL queries and knowledge of cloud-based databases like Snowflake, Redshift, BigQuery or other big data solutions ● Experience in data modelling and tools such as dbt, ETL processes, and data warehousing ● Experience with at least one of the programming languages like Python, C++[2] , Java ● Experience with version control and code review tools such as Git More ❯
operations (within the last 2 years). Degree in a financial discipline (investments, accounting, actuarial, or similar) from a UK-based university – essential . Nice-to-Haves Familiarity with dbt or Databricks. Experience with life insurance or reinsurance projects. Process Initial 20–30 minute screening interview. Follow-up 1-hour technical interview with a coding test. This is an immediate More ❯
experience is a bonus. Knowledge of data modeling (3NF, star schema, Data Vault). Experience with Python, TypeScript, or Java (Java learning expected). Familiarity with data tools like dbt or Spark; CDC tools like Debezium are a bonus. Build resilient, scalable, and observable data systems. Understanding of DevOps, Infrastructure as Code, CI/CD practices. Desirable skills Experience handling More ❯
Python: schema design, transformations, query optimisation, automation, testing. Track record of buildingETL/ELT pipelines into modern warehouses (BigQuery, Snowflake, Redshift). Familiar with tools like Dagster, Airflow, Prefect, dbt, Dataform, SQLMesh. Cloud experience (we're on GCP) + containerisation (Docker, Kubernetes). Strong sense of ownership over data standards, security, and roadmap. A collaborator at heart - working with analysts 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 ❯
modelling techniques (star schema, data vault, dimensional modelling). Proficiency in Excel-based data workflows for various Agile Retail projects. Hands-on experience with data pipeline orchestration tools (Airflow, dbt, Prefect, or similar). Benefits: Unlimited holiday Annual Wellbeing Allowance Flexible work culture Monthly socials and events Complimentary snack bar Employer pension contribution If you're a data enthusiast ready More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Office Angels
modelling techniques (star schema, data vault, dimensional modelling). Proficiency in Excel-based data workflows for various Agile Retail projects. Hands-on experience with data pipeline orchestration tools (Airflow, dbt, Prefect, or similar). Benefits: Unlimited holiday Annual Wellbeing Allowance Flexible work culture Monthly socials and events Complimentary snack bar Employer pension contribution If you're a data enthusiast ready 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 ❯
