1 to 25 of 107 Remote BigQuery Jobs in the UK

use cases. Qualifications: 5+ years of experience in analytics engineering, data engineering, or a related field. Advanced SQL skills and experience architecting solutions on modern data warehouses (e.g., Snowflake, BigQuery, Redshift). Hands-on experience with advanced modelling techniques in dbt. A deep understanding of ETL/ELT processes and tools (e.g., Fivetran, Airbyte, Stitch). Experience with data More ❯

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 technical concepts for business stakeholders Strategic More ❯

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 technical concepts for business stakeholders Strategic More ❯

commercially viable, and aligned with client expectations. Enterprise Solution Design : Architect and lead the delivery of large-scale data platforms (including lakes, lakehouses, and warehouses) using GCP, Cloud Storage, BigQuery, Databricks, Snowflake. Cloud Data Strategy: Own cloud migration and modernisation strategy, leveraging GCP, and tools such as Terraform, Azure DevOps, GitHub, and CI/CD pipelines. Data Modelling: Apply More ❯

materials for clients Present findings and recommendations to senior client stakeholders Tech Stack You'll Work With BI Tools : Power BI, Tableau, Looker, Google Data Studio Data Warehousing : Snowflake, BigQuery, Redshift, SQL Server Languages : SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks More ❯

materials for clients Present findings and recommendations to senior client stakeholders Tech Stack You'll Work With BI Tools : Power BI, Tableau, Looker, Google Data Studio Data Warehousing : Snowflake, BigQuery, Redshift, SQL Server Languages : SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks More ❯

materials for clients Present findings and recommendations to senior client stakeholders Tech Stack You'll Work With BI Tools : Power BI, Tableau, Looker, Google Data Studio Data Warehousing : Snowflake, BigQuery, Redshift, SQL Server Languages : SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks More ❯

materials for clients Present findings and recommendations to senior client stakeholders Tech Stack You'll Work With BI Tools : Power BI, Tableau, Looker, Google Data Studio Data Warehousing : Snowflake, BigQuery, Redshift, SQL Server Languages : SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks More ❯

industry best practices to continuously enhance data engineering capabilities. Looking at our current pipeline of work, we can also consider those with an Analytics Engineering lean, with experience within BigQuery (GCP) with data modelling in DBT and mobile/telecoms industry experience would be beneficial. A bit about YOU! As much as we just love working with great, fun More ❯

version control best practices in a collaborative engineering environment. Strong communicator - able to engage with both technical and non-technical colleagues. Nice to Have Skills Experience working with GCP (BigQuery) or other modern cloud-native data warehouses (e.g. Snowflake, Redshift). Familiarity with data pipelining and orchestration systems (e.g. Airflow). Understanding of modern analytics architectures and data visualisation More ❯

version control best practices in a collaborative engineering environment. Strong communicator - able to engage with both technical and non-technical colleagues. Nice to Have Skills Experience working with GCP (BigQuery) or other modern cloud-native data warehouses (e.g. Snowflake, Redshift). Familiarity with data pipelining and orchestration systems (e.g. Airflow). Understanding of modern analytics architectures and data visualisation More ❯

used backend programming languages (Python, Node.JS, Java, PHP, GO, C#, C++) Familiar with version control tools and proper branching techniques (Gitlab preferred) Experience working with data warehouses (Google Cloud BigQuery), data governance, payments and treasury or capital markets systems So, what's in it for you? Our people are constantly striving to be the best through operational excellence. The More ❯

data analytics, analytics engineering, or business intelligence, preferably in a technology or SaaS environment. Expertise in SQL and data modelling, with hands-on experience working with cloud data warehouses (BigQuery a strong plus). Proficient with BI tools (Looker Studio, Superset, or similar), able to build robust dashboards and compelling visualizations. Practical experience automating data workflows (e.g., with Python More ❯

data analytics, analytics engineering, or business intelligence, preferably in a technology or SaaS environment. Expertise in SQL and data modelling, with hands-on experience working with cloud data warehouses (BigQuery a strong plus). Proficient with BI tools (Looker Studio, Superset, or similar), able to build robust dashboards and compelling visualizations. Practical experience automating data workflows (e.g., with Python More ❯

storage and retrieval for performance Work with batch and real-time processing frameworks Implement and manage ETL processes Use tools like Python, SQL, Spark, Airflow, Kafka, dbt, Snowflake, Redshift, BigQuery Requirements Bachelors degree in Computer Science, Engineering, or a related field 1+ year in a Data Engineer or similar role Proficiency in SQL and Python (or another scripting language More ❯

storage and retrieval for performance Work with batch and real-time processing frameworks Implement and manage ETL processes Use tools like Python, SQL, Spark, Airflow, Kafka, dbt, Snowflake, Redshift, BigQuery Requirements Bachelors degree in Computer Science, Engineering, or a related field 1+ year in a Data Engineer or similar role Proficiency in SQL and Python (or another scripting language More ❯

storage and retrieval for performance Work with batch and real-time processing frameworks Implement and manage ETL processes Use tools like Python, SQL, Spark, Airflow, Kafka, dbt, Snowflake, Redshift, BigQuery Requirements Bachelors degree in Computer Science, Engineering, or a related field 1+ year in a Data Engineer or similar role Proficiency in SQL and Python (or another scripting language More ❯

CD pipelines and version control practices Nice to have: Experience using Databricks Asset Bundles (DAB) Working knowledge of GCP and/or Azure in multi-cloud environments Familiarity with BigQuery or deployment automation tools like Harness If you don't tick every box but feel you could be a great fit, we'd still love to hear from you. More ❯

a challenging start-up environment. You have a curious mind and love problem-solving. We are looking for candidates who have Demonstrable, in-depth experience with SQL, particularly in BigQuery and PostgreSQL. Proven experience with dbt, focusing on building and maintaining efficient, scalable, and reliable DAGs. Proficiency in Python for data manipulation, scripting, or automation tasks. Are proficient with More ❯

relational/non-relational databases. Proficiency in Python and/or Java for data services and API integration. Proven experience with cloud platforms (GCP preferred) and data warehouses like BigQuery or Snowflake. Strong analytical skills and experience working with large, complex datasets. Excellent communication and project management abilities. 5+ years in data engineering, ideally within fast-paced, content-driven More ❯

relational/non-relational databases. Proficiency in Python and/or Java for data services and API integration. Proven experience with cloud platforms (GCP preferred) and data warehouses like BigQuery or Snowflake. Strong analytical skills and experience working with large, complex datasets. Excellent communication and project management abilities. 5+ years in data engineering, ideally within fast-paced, content-driven More ❯

tooling, guidance, and best practices. About You: Strong technical foundation in data governance architecture and tooling. You've worked with tools such as DataHub, Apache Airflow, AWS, dbt, Snowflake, BigQuery , or similar. Hands-on experience building and maintaining centralized data inventories, business glossaries, and data mapping frameworks. Proficient in automating data classification and lineage using scripting languages like Python More ❯

Demonstrable experience deploying machine learning solutions in a production environment, and familiarity with version controls systems (e.g. Git) 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 More ❯

Demonstrable experience deploying machine learning solutions in a production environment, and familiarity with version controls systems (e.g. Git) 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 More ❯

Demonstrable experience deploying machine learning solutions in a production environment, and familiarity with version controls systems (e.g. Git) 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 More ❯