1 to 25 of 301 BigQuery Jobs

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 ❯

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 ❯

One Big Table (OBT) methodologies. • Translate business requirements from stakeholders into robust, well-documented and tested dbt models. • Develop and own workflows within Google Cloud Platform environments, primarily using BigQuery and dbt. • Write high-quality, optimised SQL for data transformation and analysis. • Develop and maintain scalable data pipelines within the Google Cloud Platform, ensuring efficient and cost-effective data 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 ❯

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 at least one programming language such as Python, Java, or Scala. Strong analytical and problem-solving skills with the ability to work independently and More ❯

technologies (e.g., Hadoop, Spark, Kafka). Proficiency in cloud platforms such as AWS, Azure, or Google Cloud and cloud-based data services (e.g., AWS Redshift, Azure Synapse Analytics, Google BigQuery). Experience with DataOps practices and tools, including CI/CD for data pipelines. Excellent leadership, communication, and interpersonal skills, with the ability to collaborate effectively with diverse teams More ❯

technologies (e.g., Hadoop, Spark, Kafka). Proficiency in cloud platforms such as AWS, Azure, or Google Cloud and cloud-based data services (e.g., AWS Redshift, Azure Synapse Analytics, Google BigQuery). Experience with DataOps practices and tools, including CI/CD for data pipelines. Excellent leadership, communication, and interpersonal skills, with the ability to collaborate effectively with diverse teams 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 ❯

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 ❯

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 infrastructure-as-code practices Familiarity with 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 ❯

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 ❯

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 infrastructure-as-code practices Familiarity with More ❯

and non-technical stakeholders alike. The Head of Data Engineering & Insight will work within a modern, cloud-based BI ecosystem , including: Data Integration: Fivetran , HVR, Databricks , Apache Kafka, Google BigQuery , Google Analytics 4 Data Lake & Storage: Databricks Delta Lake, Amazon S3 Data Transformation: dbt Cloud Data Warehouse: Snowflake Analytics & Reporting: Power BI, Excel, Snowflake SQL REST API Advanced Analytics More ❯

and non-technical stakeholders alike. The Head of Data Engineering & Insight will work within a modern, cloud-based BI ecosystem , including: Data Integration: Fivetran , HVR, Databricks , Apache Kafka, Google BigQuery , Google Analytics 4 Data Lake & Storage: Databricks Delta Lake, Amazon S3 Data Transformation: dbt Cloud Data Warehouse: Snowflake Analytics & Reporting: Power BI, Excel, Snowflake SQL REST API Advanced Analytics 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 ❯

either leverage third party tools such as Fivetran, Airbyte, Stitch or build custom pipelines. We use the main data warehouses for dbt modelling and have extensive experience with Redshift, BigQuery and Snowflake. Recently we've been rolling out a serverless implementation of dbt and progressing work on internal product to build modular data platforms. When initially working with clients More ❯