1 to 25 of 88 Remote Permanent BigQuery Jobs

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

Engineering/Data Engineering/BI Engineering experience Understanding of data warehousing, data modelling concepts and structuring new data tables Knowledge of cloud-based MPP data warehousing (e.g. Snowflake, BigQuery, Redshift) Nice to have Experience developing in a BI tool (Looker or similar) Good practical understanding of version control SQL ETL/ELT knowledge, experience with DAGs to manage More ❯

Deep technical expertise in software and data engineering, programming languages (python, java etc.). Understanding of orchestration (Composer, DAGs), data processing (Kafka, Flink, DataFlow, dbt), and database capabilities (e.g. BigQuery, CloudSQL, BigTable). Container technologies (Docker, Kubernetes), IaaC (Terraform) and experience with cloud platforms such as GCP. CI/CD: Detailed understanding of working automated CI/CD pipelines More ❯

ETL/ELT Pipelines: Proven experience designing, building, and maintaining production-grade data pipelines using Google Cloud Dataflow (Apache Beam) or similar technologies. GCP Stack: Hands-on expertise with BigQuery , Cloud Storage , Pub/Sub , and orchestrating workflows with Composer or Vertex Pipelines. Data Architecture & Modelling: Ability to translate diverse business requirements into scalable data models and architect a More ❯

ETL/ELT Pipelines: Proven experience designing, building, and maintaining production-grade data pipelines using Google Cloud Dataflow (Apache Beam) or similar technologies. GCP Stack: Hands-on expertise with BigQuery , Cloud Storage , Pub/Sub , and orchestrating workflows with Composer or Vertex Pipelines. Data Architecture & Modelling: Ability to translate diverse business requirements into scalable data models and architect a More ❯

influence others and present to both technical and non-technical stakeholders Strong hands-on experience with analytics and data tools, including Google Tag Manager, Google Analytics, Tableau, Excel, Google BigQuery, and a solid understanding of SQL Familiarity with dashboard design and best practices, especially for executive and operational audiences Commercially minded and data-driven, with a passion for applying More ❯

each use case Support knowledge sharing and technical best practice Essential Experience: Proven expertise in building data warehouses and ensuring data quality on GCP Strong hands-on experience with BigQuery, Dataproc, Dataform, Composer, Pub/Sub Skilled in PySpark, Python and SQL Solid understanding of ETL/ELT processes Clear communication skills and ability to document processes effectively Desirable More ❯

data solutions Migrating from Azure to GCP Automate data lifecycle processes and optimise cloud resource usage Support analytics and self-service reporting initiatives Skills & Experience Strong experience with GCP, BigQuery, Dataflow Proficiency in Python and Terraform Skilled in ETL/ELT, data modelling, and metadata management Familiarity with CI/CD, DevOps, and Infrastructure-as-Code Knowledge of insurance More ❯

data solutions Migrating from Azure to GCP Automate data lifecycle processes and optimise cloud resource usage Support analytics and self-service reporting initiatives Skills & Experience Strong experience with GCP, BigQuery, Dataflow Proficiency in Python and Terraform Skilled in ETL/ELT, data modelling, and metadata management Familiarity with CI/CD, DevOps, and Infrastructure-as-Code Knowledge of insurance More ❯

systems (Kafka, Spark Streaming, Kinesis) Familiarity with schema design and semi-structured data formats Exposure to containerisation, graph databases, or machine learning concepts Proficiency with cloud-native data tools (BigQuery, Redshift, Snowflake) Enthusiasm for learning and experimenting with new technologies Why Join Capco Deliver high-impact technology solutions for Tier 1 financial institutions Work in a collaborative, flat, and 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 ❯

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 ❯