1 to 25 of 92 BigQuery Jobs in the South East

data science libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Expertise in multi-cloud environments (AWS, Azure, GCP) including services like S3, BigQuery, Azure ML, etc. Solid understanding of data engineering principles, SQL, and distributed computing frameworks (Spark, Hadoop). Experience in consulting or client-facing roles, with ability ...

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 ...

clarify requirements and translate them into model updates Skills & Experience You should have: Strong SQL skills and experience working with cloud data warehouses (BigQuery, Redshift, Snowflake, etc.) Solid experience building models and transformations using dbt Understanding of dimensional modelling and data transformation principles Exposure to BI tools (Looker, Power ...

maintain scalable ETL/ELT pipelines for ingestion, transformation, and validation Develop data models and implement storage solutions such as S3, Azure Blob, BigQuery or Snowflake Apply data quality checks and prepare datasets for reporting, analytics and visualisation Support data governance, standards, anonymisation and security best practice Monitor, tune ...

Qualifications & Experience Essential Advanced SQL skills with strong data modelling expertise (facts, dimensions, semantic layers). Experience working with modern cloud data warehouses (e.g. BigQuery, Snowflake, Redshift). Hands-on experience with analytics engineering tools (e.g. dbt). Strong understanding of ELT pipelines and data transformation best practices. Ability ...

months to align legacy stacks with modern standards What they are looking for Technical experience Strong SQL experience with Redshift or BigQuery and exposure to Snowflake or another modern warehouse Proven experience building production dbt models, tests, and environments Solid understanding of dimensional modelling and Kimball principles Experience working ...

clients to present insights and actionable recommendations. Platforms You'll Work With: Google Analytics 4 (GA4) Google Tag Manager (GTM) Google Marketing Platform BigQuery & SQL Looker Studio Tools like Supermetrics, Power BI, Tableau, and CRM systems like Salesforce What We're Looking For: Experience in marketing analytics ...

e.g. Python ELT/ETL CI/CD Data Modelling Data Architecture Data Frameworks dbt Data processing and orchestration using Airflow or similar Google BigQuery or Redshift Cloud based services: GCP (preferred) or AWS Agentic development frameworks Automations About You 6 years+ experience as a Data Engineer solving complex ...

using SQL and Python to uncover trends and guide strategic decision-making. Build and maintain KPI dashboards using modern BI tools (e.g., Looker Studio, BigQuery). Maintain high data quality through validation, monitoring and governance best practices. Contribute to the development and optimisation of the analytics and data warehouse ...

. Promote self-service analytics and data literacy across the business. Act as an expert in SQL across technologies like Postgres, Cloud SQL, BigQuery, and Redshift . Build and orchestrate pipelines using Airflow . Support IaC and CI/CD best practices via GitHub. Work closely with data engineers ...

future of cloud-powered, AI-driven analytics with a team operating at the cutting edge of data and marketing tech. You'll work with: BigQuery Cloud Functions Dataflow Analytics Hub Looker Studio APIs & Python What we're looking for: Strong GCP data engineering experience Building & optimising data pipelines/ ...

Google Cloud Storage preferred) Support PyTorch-based workflows, particularly around data loading and dataset management in the cloud Build and optimise data integrations with BigQuery and SQL databases Ensure efficient memory usage and performance when handling large datasets Collaborate with ML engineers to support training and experimentation pipelines (without ...

Technology/Skills requirements SQL ELT/ETL Data Modelling dbt models Version control (Git) Data processing and orchestration using Airflow or similar Google BigQuery or Redshift Cloud based services: GCP (preferred) or AWS Agentic development frameworks Automations About You 4 years+ experience as a Data Engineer solving complex ...

workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced ...

workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced ...

workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced ...

workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced ...

workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced ...

workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced ...

workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced ...

workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced ...

workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced ...

workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced ...

workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced ...

workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced ...