1 to 25 of 106 Remote BigQuery Jobs in the UK

engineers, data scientists, and business stakeholders. Familiarity with cloud-based data ecosystems such as AWS, Azure, or GCP, and working with data warehouse/lakehouse technologies such as Snowflake, BigQuery, Redshift, or Athena/Glue. Essential: Proficient in writing clean, efficient, and maintainable SQL and Python code, particularly for data transformation and analytics use cases. Strong understanding of data More ❯

engineers, data scientists, and business stakeholders. Familiarity with cloud-based data ecosystems such as AWS, Azure, or GCP, and working with data warehouse/lakehouse technologies such as Snowflake, BigQuery, Redshift, or Athena/Glue. Essential: Proficient in writing clean, efficient, and maintainable SQL and Python code, particularly for data transformation and analytics use cases. Strong understanding of data More ❯

engineers, data scientists, and business stakeholders. Familiarity with cloud-based data ecosystems such as AWS, Azure, or GCP, and working with data warehouse/lakehouse technologies such as Snowflake, BigQuery, Redshift, or Athena/Glue. Essential: Proficient in writing clean, efficient, and maintainable SQL and Python code, particularly for data transformation and analytics use cases. Strong understanding of data More ❯

engineers, data scientists, and business stakeholders. Familiarity with cloud-based data ecosystems such as AWS, Azure, or GCP, and working with data warehouse/lakehouse technologies such as Snowflake, BigQuery, Redshift, or Athena/Glue. Essential: Proficient in writing clean, efficient, and maintainable SQL and Python code, particularly for data transformation and analytics use cases. Strong understanding of data More ❯

engineers, data scientists, and business stakeholders. Familiarity with cloud-based data ecosystems such as AWS, Azure, or GCP, and working with data warehouse/lakehouse technologies such as Snowflake, BigQuery, Redshift, or Athena/Glue. Essential: Proficient in writing clean, efficient, and maintainable SQL and Python code, particularly for data transformation and analytics use cases. Strong understanding of data More ❯

promised outcomes. Drive high client value and broaden relationships at senior levels with current and prospective clients. Our Tech Stack Cloud: Azure, sometimes GCP & AWS Data Platform: Databricks, Snowflake, BigQuery Data Engineering tools: Pyspark, Polars, DuckDB, Malloy, SQL Infrastructure-as-code: Terraform, Pulumi Data Management and Orchestration: Airflow, dbt Databases and Data Warehouses: SQL Server, PostgreSQL, MongoDB, Qdrant, Pinecone More ❯

rail industry's revenue allocation system through a suite of technology upgrades and methodological improvements. Key enhancements include migrating the platform to Google Cloud Platform (GCP), implementing a modern BigQuery-based Data Warehouse, and replacing the legacy solution for allocation factor calculation with an innovative, graph database-driven solution. Duties: Lead the design of data architectures and the development More ❯

components Programming experience in Python Skills and experience we’d love you to have... Understanding of cloud computing security concepts Experience in relational cloud based database technologies like Snowflake, BigQuery, Redshift Experience in open source technologies like Spark, Kafka, Beam Good understanding of Cloud providers – AWS, Microsoft Azure, Google Cloud Familiarity with DBT, Delta Lake, Databricks Experience working in More ❯

components Programming experience in Python Skills and experience we’d love you to have... Understanding of cloud computing security concepts Experience in relational cloud based database technologies like Snowflake, BigQuery, Redshift Experience in open source technologies like Spark, Kafka, Beam Good understanding of Cloud providers – AWS, Microsoft Azure, Google Cloud Familiarity with DBT, Delta Lake, Databricks Experience working in 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 ❯

and architecture, with a focus on developing scalable cloud solutions in Azure, GCP or AWS. Data Modelling using Kimball, 3NF or Dimensional methodologies Analytics Engineering lean, with experience within BigQuery (GCP) with data modelling in DBT and mobile/telecoms industry experience would be beneficial, with deep DBT experience being highly beneficial Depth of knowledge and understanding across core More ❯

beverages Requirements Highly proficient in SQL Highly proficient in Python Strong understanding of data modelling techniques, e.g. 3NF, Kimball Experience using cloud-based data platforms and infrastructure, e.g. Snowflake, BigQuery etc Experience building data integrations and understanding of best practices Understanding of the development lifecycle and best practices Desire to build relationships with an ability to deliver solutions to More ❯

modern data lake architectures Advanced proficiency in Python (including PySpark) and SQL, with experience building scalable data pipelines and analytics workflows Strong background in cloud-native data infrastructure (e.g., BigQuery, Redshift, Snowflake, Databricks) Demonstrated ability to lead teams, set technical direction, and collaborate effectively across business and technology functions Desirable skills Familiarity with machine learning pipelines and MLOps practices More ❯

Data Science, or a related field. 5+ years of experience in data architecture, solution design, or similar roles. Strong experience with modern data platforms and technologies (e.g., Snowflake, Databricks, BigQuery, Azure/AWS/GCP data services). Deep knowledge of data modeling, APIs, event-driven architectures, and cloud-native data architectures. Proven ability to design and implement scalable More ❯

Data Science, or a related field. 5+ years of experience in data architecture, solution design, or similar roles. Strong experience with modern data platforms and technologies (e.g., Snowflake, Databricks, BigQuery, Azure/AWS/GCP data services). Deep knowledge of data modeling, APIs, event-driven architectures, and cloud-native data architectures. Proven ability to design and implement scalable More ❯

Data Science, or a related field. 5+ years of experience in data architecture, solution design, or similar roles. Strong experience with modern data platforms and technologies (e.g., Snowflake, Databricks, BigQuery, Azure/AWS/GCP data services). Deep knowledge of data modeling, APIs, event-driven architectures, and cloud-native data architectures. Proven ability to design and implement scalable More ❯

equivalent (expired is acceptable) Working knowledge of SQL and data modelling concepts Experience with BI tools (e.g., Power BI, Looker, Tableau) Familiarity with cloud data platforms such as Snowflake, BigQuery, or AWS Redshift Understanding of modern data architecture and APIs Our Offer Flexi-Week and Work-Life Balance: We prioritise your mental health and wellbeing, offering you a flexible More ❯

joins) Hands-on experience designing and deploying ETL/ELT pipelines using Google Cloud Dataflow (Apache Beam) or similar tools Strong command of the Google Cloud Platform (GCP) stack: BigQuery, Cloud Storage, Pub/Sub, Composer, or Vertex Pipelines Proficiency in data architecture, data modeling, and scalable storage design Solid engineering practices: Git and CI/CD for data More ❯

joins) Hands-on experience designing and deploying ETL/ELT pipelines using Google Cloud Dataflow (Apache Beam) or similar tools Strong command of the Google Cloud Platform (GCP) stack: BigQuery, Cloud Storage, Pub/Sub, Composer, or Vertex Pipelines Proficiency in data architecture, data modeling, and scalable storage design Solid engineering practices: Git and CI/CD for data More ❯

joins) Hands-on experience designing and deploying ETL/ELT pipelines using Google Cloud Dataflow (Apache Beam) or similar tools Strong command of the Google Cloud Platform (GCP) stack: BigQuery, Cloud Storage, Pub/Sub, Composer, or Vertex Pipelines Proficiency in data architecture, data modeling, and scalable storage design Solid engineering practices: Git and CI/CD for data More ❯

joins) Hands-on experience designing and deploying ETL/ELT pipelines using Google Cloud Dataflow (Apache Beam) or similar tools Strong command of the Google Cloud Platform (GCP) stack: BigQuery, Cloud Storage, Pub/Sub, Composer, or Vertex Pipelines Proficiency in data architecture, data modeling, and scalable storage design Solid engineering practices: Git and CI/CD for data More ❯

joins) Hands-on experience designing and deploying ETL/ELT pipelines using Google Cloud Dataflow (Apache Beam) or similar tools Strong command of the Google Cloud Platform (GCP) stack: BigQuery, Cloud Storage, Pub/Sub, Composer, or Vertex Pipelines Proficiency in data architecture, data modeling, and scalable storage design Solid engineering practices: Git and CI/CD for data More ❯

Reporting and Data Engineering team in maintaining consistent and accurate data. What do we need from you? Experience with either relational SQL or analytics databases, including Postgres, Cassandra and BigQuery Familiarity with cloud-based technologies and deployment infrastructure such as GCP functions, Kubernetes & Terraform/Jenkins, CI/CD Git. Knowledge of Data Modelling, ETL development and Database/ More ❯

technical topics for non-technical audiences. Team player - Collaborative, curious, and happy to work in a self-organising, fast-paced environment. Nice-to-Have Skills : Experience with GCP/BigQuery or other cloud data warehouses (e.g., Snowflake, Redshift). Familiarity with data orchestration tools (e.g., Airflow). Experience with data visualisation platforms (such as Preset.io/Apache Superset or More ❯

technical topics for non-technical audiences. · Team player - Collaborative, curious, and happy to work in a self-organising, fast-paced environment. Nice-to-Have Skills : ·Experience with GCP/BigQuery or other cloud data warehouses (e.g., Snowflake, Redshift). ·Familiarity with data orchestration tools (e.g., Airflow). ·Experience with data visualisation platforms (such as Preset.io/Apache Superset or More ❯