26 to 50 of 291 BigQuery Jobs in the UK

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

stakeholders and deliver high-quality outputs under deadlines. Strong business acumen and ability to connect data to commercial outcomes. Strong experience with data warehousing and cloud platforms (e.g. Azure, BigQuery, Teradata) required About Primark At Primark, people matter. They're the beating heart of our business and the reason we've grown from our first store in Dublin in 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 ❯

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 ❯

expertise to grow top line revenues and guide commercial initiatives from our data. You'll own the analysis of the end-to-end customer journey, using our data stack ( BigQuery, dbt, Hex ) to create data models, data products, metrics and find insights that fuel our growth. You'll work closely with other engineers, marketers, product teams, and commercial teams 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 ❯

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 ❯

management practices, system development life cycle management, IT services management, agile and lean methodologies, infrastructure and operations, and EA and ITIL frameworks. Proficiency with data warehousing solutions (e.g., Google BigQuery, Snowflake). Expertise in data modeling tools and techniques (e.g., SAP PowerDesigner, EA Sparx). Strong knowledge of SQL and NoSQL databases (e.g., MongoDB, Cassandra). Familiarity with cloud More ❯

marketing analytics for Marketing Mix Modelling, Forecasting, and Predictive Analysis. Experience with data transformation and parsing using SQL queries, Python, or R. Experience with cloud data warehouses (e.g., Snowflake, BigQuery), visualization tools (e.g., Tableau, Looker), and web analytics platforms. If you believe you have the relevant experience, please reply to this advert or email your CV to Not right More ❯

global retail or similar data-intensive industry Expert-level proficiency in various data modeling techniques and tools Strong hands-on experience with cloud data platforms, specifically Google Cloud Platform - BigQuery Experience with leading ETL/ELT tools and data pipeline orchestration (e.g., Dataflow, Apache Airflow, Talend, Informatica) Advanced SQL skills and deep knowledge of various database technologies (relational, columnar More ❯

advance measurement methodologies Proficiency in common data science coding languages such as in SQL, Python and/or R Practical experience with Google Cloud Platform and services such as BigQuery, Looker, and DataProc Additional Information The Power of One starts with our people! To do powerful things, we offer powerful resources. Our best-in-class wellness and benefits offerings More ❯

transforming and modeling data Airflow for orchestrating workflows Fivetran for data extraction and integration Erwin for data modeling and documentation Strong understanding of relational databases and SQL (PostgreSQL, Snowflake, BigQuery, etc.). Familiarity with cloud platforms (AWS, GCP, or Azure). Experience working with large-scale datasets and complex ETL/ELT processes. Excellent problem-solving and communication skills. More ❯

Engineering/BI Engineering experience Excellent SQL skills 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯