1 to 25 of 67 Remote Permanent BigQuery Jobs

Google Cloud Platform, including core services, architecture patterns, and best practices. Cloud Database Technologies: Expertise in cloud-native databases (Amazon Aurora, Azure SQL Database, Google Cloud SQL, Cosmos DB, BigQuery) and distributed database systems. Infrastructure as Code (IaC): Proficient in Terraform, ARM templates, CloudFormation, or similar tools for automated infrastructure deployment and management. Database Administration: Advanced skills in SQL 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 beneficialDepth of knowledge and understanding across core orchestration More ❯

processing and analytics. Hands-on experience in data integration , including designing and optimising data pipelines (batch and streaming) and integrating cloud-based platforms (e.g., Azure Synapse, AWS Redshift, Google BigQuery ) with legacy systems, ensuring performance and scalability. Deep knowledge of ETL/ELT processes , leveraging tools like Apache Airflow, dbt, or Informatica , with a focus on ensuring data quality More ❯

engineering and architecture, with a focus on developing scalable cloud solutions in Azure, GCP or AWS. Data Modelling using Kimball, 3NF or Dimensional methodologiesAnalytics 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 beneficialDepth of knowledge and understanding across core orchestration 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 ❯

in data architecture, data modeling, and scalable storage design Solid engineering practices: Git and CI/CD for data systems Highly Desirable Skills GCP Stack: Hands-on expertise with BigQuery, Cloud Storage, Pub/Sub, and orchestrating workflows with Composer or Vertex Pipelines. Domain Knowledge: Understanding of sports-specific data types ( event, tracking, scouting, video ) API Development: Experience building More ❯

in data architecture, data modeling, and scalable storage design Solid engineering practices: Git and CI/CD for data systems Highly Desirable Skills GCP Stack: Hands-on expertise with BigQuery, Cloud Storage, Pub/Sub, and orchestrating workflows with Composer or Vertex Pipelines. Domain Knowledge: Understanding of sports-specific data types ( event, tracking, scouting, video ) API Development: Experience building More ❯

in data architecture, data modeling, and scalable storage design Solid engineering practices: Git and CI/CD for data systems Highly Desirable Skills GCP Stack: Hands-on expertise with BigQuery, Cloud Storage, Pub/Sub, and orchestrating workflows with Composer or Vertex Pipelines. Domain Knowledge: Understanding of sports-specific data types ( event, tracking, scouting, video ) API Development: Experience building More ❯

and Python . Strong grasp of ETL/ELT pipelines , data modeling , and data warehousing . Experience with cloud platforms (AWS, Azure, GCP) and tools like Snowflake, Databricks, or BigQuery . Familiarity with streaming technologies (Kafka, Spark Streaming, Flink) is a plus. Tools & Frameworks: Airflow, dbt, Prefect, CI/CD pipelines, Terraform. Mindset: Curious, data-obsessed, and driven to 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 ❯

particularly in data modelling. Strong SQL and hands-on dbt experience. Ability to convert business requirements into logical, scalable data models. Knowledge of cloud data platforms (e.g., Snowflake, Redshift, BigQuery). Strong communication and documentation skills. Structured, detail-oriented mindset. Desirable: Experience with semantic modelling tools (e.g., dbt SL, LookML). Familiarity with workflow orchestration and BI tooling. Version More ❯

Analysts, and cross-functional squads to land scalable data solutions. Mentor mid-level analysts on analytics delivery, tooling, and stakeholder engagement. Work with a modern data stack, including Redshift, BigQuery, Matillion, and Retool Location This role is based can be based in London or Nuneaton, and may be occasionally required to travel to any other location of H&B. More ❯

Strong SQL skills and mastery of Dataform , with experience designing clean, performant, and modular data models supporting attribution and funnel analysis. Deep experience with Google Cloud Platform (GCP) , particularly BigQuery , including cost- and performance-optimized schema design. Advanced knowledge of Customer Data Platforms (Segment.io) , including event stream management, identity resolution, and building a "Golden Profile." Hands-on experience designing More ❯

strategy. You can tackle loosely defined problems and come up with relevant analytical approaches and impactful insights. You have proficiency with Python, or similar programming languages, experience with Google BigQuery & expertise in SQL. You have hands-on knowledge of A/B testing methodologies and experimentation at scale, including application of this knowledge to digital products. You enjoy sharpening More ❯

you're going to need Deep, hands-on experience designing and building data warehouses with strong command of dimensional modeling (e.g., Kimball methodology) Expertise in Google Cloud Platform, especially BigQuery architecture, optimization, and cost management Advanced SQL skills and production-level experience using dbt (or similar tools) to build modular, testable transformation pipelines Practical mastery of LookML and semantic More ❯

Promotions teams to deliver data products. Contribute to sprint planning and backlog shaping as part of the Commercial Ops analytics roadmap. Work with a modern data stack, including Redshift, BigQuery, Matillion, and Retool. Location: This is a hybrid role, with 2 days per week expected in either our Nuneaton office (CV10 7RH) The Person What We're Looking For More ❯

Requirements About You Proficient in SQL, with experience querying and transforming large datasets across marketing, sales, and customer data sources. Comfortable working with modern data stacks, ideally including Redshift, BigQuery, Matillion, Metabase, and Retool. Strong grasp of performance marketing metrics such as ROAS, CAC, CTR, CPM, and attribution models. Experienced in building dashboards and visualisations that enable data-driven More ❯

with middleware tools like Tray, Zapier, Make, n8n, and SuperBlocks, and extensive experience with rETL platforms and architecture (Polytomic, Hightouch, RudderStack, etc.) Familiarity with data warehouse platforms like Snowflake, BigQuery, DataBricks, etc. Bonus If You: Experience with other types of data storage ranging cache tools like Redis to S3 Built systems integrating data from a variety of tools and More ❯

with the ability to effectively present findings to both technical and non-technical stakeholders. Experience of A/B testing, experience in running retailed-based tool analytics Experience of BigQuery is desirable Benefits Pension company contribution = 3% Incentive scheme up to 10% of annual salary , based on company performance. Your wellbeing is paramount so you can get away and More ❯

web or mobile app experiences. Excellent communication and stakeholder management. What Will Make You Stand Out: Proficiency in SQL and experience with cloud data platforms (e.g. Google Cloud Platform , BigQuery ). If interested please apply, to follow up on your application email or message me on LinkedIn. More ❯

with a multi-person engineering team, leveraging modern practices like code reviews, CI/CD, and trunk-based development. Experience in cloud ecosystems, particularly Google Cloud Platform services like BigQuery, Pub/Sub, or Cloud Functions. Required Skills/Abilities Proficiency in software development using modern programming languages like Python, Java, Go, or similar tools. Strong understanding of microservices More ❯

of S3, RDS, Kinesis, EC2, EMR, ElastiCache, ElasticSearch and EKS). Elements of the platform will start to expand into GCP (Compute Engine, Cloud Storage, Google Kubernetes Engine and BigQuery). Other significant tools of the platform include Linux, Terraform, Kubernetes, Docker, Packer, Ansible and Jenkins. We support applications and services written in Golang, Python, Java, Scala and .Net. More ❯

Solid SQL/BQ skills for data querying and manipulation. Extensive experience with Google Cloud Platform (GCP) AI/ML services is highly desirable (e.g. Vertex AI, Cloud Functions, BigQuery). Deep understanding of machine learning algorithms and techniques, including deep learning, natural language processing, computer vision, regression, classification, and clustering. Experience with evaluating and selecting different LLMs (Large More ❯