1 to 25 of 300 BigQuery Jobs in the UK

with big data technologies (e.g., Hadoop, Spark, Kafka). Familiarity with AWS and its data services (e.g. S3, Athena, AWS Glue). Familiarity with data warehousing solutions (e.g., Redshift, BigQuery, Snowflake). Knowledge of containerization and orchestration tools (e.g., Docker, ECS, Kubernetes). Familiarity of data orchestration tools (e.g. Prefect, Apache Airflow). Familiarity with CI/CD pipelines More ❯

such as MySQL, PostgreSQL, or Oracle. Experience with big data technologies such as Hadoop, Spark, or Hive. Familiarity with data warehousing and ETL tools such as Amazon Redshift, Google BigQuery, or Apache Airflow. Proficiency in Python and at least one other programming language such as Java, or Scala. Willingness to mentor more junior members of the team. Strong analytical More ❯

similar (for real-time data streaming) Experience using data tools in at least one cloud service - AWS, Azure or GCP (e.g. S3, EMR, Redshift, Glue, Azure Data Factory, Databricks, BigQuery, Dataflow, Dataproc Would you like to join us as we work hard, have fun and make history? Apply for this job indicates a required field First Name Last Name More ❯

similar (for real-time data streaming) Experience using data tools in at least one cloud service - AWS, Azure or GCP (e.g. S3, EMR, Redshift, Glue, Azure Data Factory, Databricks, BigQuery, Dataflow, Dataproc) Would you like to join us as we work hard, have fun and make history? Apply for this job indicates a required field First Name Last Name More ❯

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 ❯

similar scripting languages for data science Experience with data processes and building ETL pipelines Experience with cloud data warehouses such as Snowflake, Azure Data Warehouse, Amazon Redshift, or Google BigQuery Proficiency in creating visualizations using Power BI or Tableau Experience designing ETL/ELT solutions with tools like SSIS, Alteryx, AWS Glue, Databricks, IBM DataStage Strong analytical and technical 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 ❯

ERP systems (e.g., Salesforce, Netsuite, or similar). Strong grasp of data governance, quality assurance, and security best practices. Bonus: Experience with Microsoft Fabric, cloud data warehouses (Azure, Snowflake, BigQuery, Redshift), or orchestration tools like dbt or Airflow. Collaboration & Communication Ability to communicate technical insights clearly to non-technical audiences. Experience partnering with leadership and cross-functional teams. Mindset More ❯

ERP systems (e.g., Salesforce, Netsuite, or similar). Strong grasp of data governance, quality assurance, and security best practices. Bonus: Experience with Microsoft Fabric, cloud data warehouses (Azure, Snowflake, BigQuery, Redshift), or orchestration tools like dbt or Airflow. Collaboration & Communication Ability to communicate technical insights clearly to non-technical audiences. Experience partnering with leadership and cross-functional teams. Mindset More ❯

big data platforms. Knowledge of data modeling, replication, and query optimization. Hands-on experience with SQL and NoSQL databases is desirable. Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) would be beneficial. Data Platform Management: Comfortable operating in hybrid environments (cloud and on-prem). Experience integrating diverse data sources and systems. Understanding of secure data transfer protocols More ❯

of experience in data engineering, analytics engineering, or a similar technical data role Advanced skills in SQL and Python Proven experience with cloud data warehousing platforms like Redshift, Databricks, BigQuery, or Snowflake Experience building and maintaining ELT pipelines using dbt in a production environment Strong understanding of data modelling principles (e.g., bronze/silver/gold layer design) Hands More ❯

big data platforms. Knowledge of data modeling, replication, and query optimization. Hands-on experience with SQL and NoSQL databases is desirable. Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) would be beneficial. Data Platform Management: Comfortable operating in hybrid environments (cloud and on-prem). Experience integrating diverse data sources and systems. Understanding of secure data transfer protocols More ❯

Streams)? Select Which statement best describes your hands on responsibility for architecting and tuning cloud native data lake/warehouse solutions (e.g., AWS S3 + Glue/Redshift, GCP BigQuery, Azure Synapse)? Select What best reflects your experience building ETL/ELT workflows with Apache Airflow (or similar) and integrating them into containerised CI/CD pipelines (Docker, GitHub More ❯

the ability to upskill team members through peer review, training, and best practice development. Data Infrastructure: A solid understanding of cloud-based data warehousing (e.g., Azure, Fabric, Snowflake, Redshift, BigQuery) and ETL processes. Analytical Prowess: Exceptional analytical and problem-solving skills, with the ability to translate complex data into clear, actionable business insights. Demonstrated proficiency in Python/R More ❯

NiFi, Talend). Strong understanding of relational databases and SQL. Experience with cloud platforms (e.g., AWS, GCP, Azure) and their data services. Familiarity with data warehousing solutions (e.g., Redshift, BigQuery, Snowflake). Experience with version control systems (e.g., Git). Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills. Preferred Qualifications: Experience with containerization and More ❯

Strong SQL Server skills, including query optimisation and performance tuning. Familiarity with scheduling and orchestration tools (e.g. Control-M). Hands-on experience with Google Cloud tools such as BigQuery, Composer, and VertexAI. Proficient in Python for data manipulation and modelling. Strong skills in data visualisation using Tableau Desirable: Background in insurance or financial services, with exposure to industry More ❯

you have Experience in the gaming industry Experience with event-driven applications Exposure to CI/CD pipelines and automated testing for data infrastructure Experience with additional data warehouses (BigQuery, Snowflake, etc. More ❯

statistics (hypothesis testing, regression, significance, p-value pitfalls) Ability to translate data into plain-English insights and present to C-level audiences Experience working in cloud data warehouses (Snowflake, BigQuery, Redshift) and version control (Git) What we can offer Bonus Hybrid working; meaning you'll be in our Farringdon office Tuesdays to Thursdays 25 days annual leave, plus the 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 ❯

with Looker and LookML, demonstrating a strong understanding of data modeling, visualization, and reporting techniques. Proficiency in SQL and a good understanding of relational database concepts. Experience working with BigQuery as a data warehouse, preferably in a cloud-based environment. Familiarity with ETL/ELT processes and tools, such as Dataflow and Cloud Data Fusion, for data integration and More ❯

to hierarchically structure information residing in the data under analysis. Robust knowledge of statistical concepts, accompanied by expertise with a set of analytical tools ranging from databases (e.g. SQL, BigQuery, noSQL) to programming languages (e.g. R, Python), and from data visualisation (e.g. Tableau, PowerBI) to machine learning. Understanding data engineering solutions is a plus. Strong experience in MLOps, including More ❯

of at least one database technology (relational, columnar, or NoSQL) and familiarity with others (e.g., MySQL, Oracle, MSSQL, Vertica, MongoDB) Knowledge of cloud data warehouses like Snowflake, Databricks, and BigQuery Proven ability to manage technical project delivery, including scoping, planning, and risk assessment Strong organisational skills to oversee multiple concurrent customer projects Adaptability to shifting customer requirements and priorities More ❯