1 to 25 of 151 BigQuery Jobs

or GCP) and cloud-native BI services. Strong understanding of data warehousing, OLAP, semantic models, and query optimization. Experience working with modern data platforms such as Snowflake, Databricks, Redshift, BigQuery, or Synapse. Soft Skills Excellent communication and collaboration skills. Ability to lead technical teams and manage multiple workstreams. Strong problem-solving, analytical thinking, and decision-making skills. Ability to More ❯

an Analytics Engineer, Data Modeller, or similar position in a modern cloud-based data environment. Strong SQL skills and hands-on experience with platforms such as Snowflake, Azure Synapse, BigQuery, or Redshift. Deep understanding of Data Vault, Kimball, and dimensional modelling techniques. Experience designing data marts and semantic layers for BI tools (Power BI, Tableau, Looker). Familiarity with More ❯

in SQL, NoSQL and data integration technologies. Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud. Experience with data warehousing technologies such as Snowflake, Redshift, BigQuery, Synapse, or Teradata. Skilled in ETL/ELT tools and data pipeline technologies such as Informatica, Talend, Databricks, or Apache tools. Strong understanding of data governance, MDM, metadata management More ❯

HBase, etc. Strong experience with Cloud platforms (AWS/Azure/GCP) and services like: AWS: S3, Glue, EMR, Redshift, Lambda, Kinesis Azure: Data Factory, Synapse, Databricks, ADLS GCP: BigQuery, Dataflow, Pub/Sub Experience with Data Warehouse/Data Lake/Lakehouse design and modeling (Kimball, OLAP, OLTP, Star/Snowflake schemas Proficiency in CI/CD, Git More ❯

Java, strong SQL skills, and knowledge of big data tools like Apache Hadoop, Spark, or Kafka. Experience with cloud platforms (AWS, Azure, GCP) and data warehousing solutions (Snowflake, Redshift, BigQuery) Self-driven and have demonstrated the ability to work independently with minimum guidance Demonstrated multitasking ability, problem solving skills and a consistent record of on time delivery and customer More ❯

Python, Scala, or Java for data engineering tasks.Experience with big data tools (Spark, Hadoop, Kafka, FlinkKnowledge of ETL/ELT tools (Airflow, dbt, Glue, InformaticaFamiliarity with data warehousing (Snowflake, BigQuery, RedshiftUnderstanding of data modeling, normalization, and data governance.Experience with Git, CI/CD, and cloud platforms (AWS/GCP/Azure Preferred Qualifications Experience with streaming technologies (Kafka, Kinesis More ❯

MLFlow, Kubeflow, Docker, Kubernetes, Terraform, GitHub Actions Data & Integration: SQL, NoSQL, Snowflake, Databricks, Airflow, MuleSoft, Boomi, REST APIs Cloud Platforms: AWS (SageMaker, Lambda), Azure (ML Studio), GCP (Vertex AI, BigQuery More ❯

Bell’s Data Governance and Data Classification policies. Maintain data dictionary. Maintain business level data model. Recommending and introducing new technology where needed. Core: Cloud data platforms (e.g. Snowflake, BigQuery, Redshift) Data transformation technology such as DBT Visual Studio Code Python CI automation systems such as Jenkins A git-based source control system such as BitBucket Data Warehouse/ More ❯

AJ Bells Data Governance and Data Classification policies. Maintain data dictionary. Maintain business level data model. Recommending and introducing new technology where needed. Core: Cloud data platforms (e.g. Snowflake, BigQuery, Redshift) Data transformation technology such as DBT Visual Studio Code Python CI automation systems such as Jenkins A git-based source control system such as BitBucket Data Warehouse/ More ❯

the following tools and technologies (note we do not expect applicants to have prior experience of all them): Google Cloud Platform for all of our analytics infrastructure dbt and BigQuery SQL for our data modelling and warehousing Python for data science Go to write our application code AWS for most of our backend infrastructure You should apply if: What 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 ❯

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 ❯

for guidance. Strong SQL skills and understanding of data models and data principles. Experience with mobile-responsive dashboards and self-service analytics. Desirable Experience with cloud platforms (Snowflake, Azure, BigQuery). Python skills. Experience in agile delivery environments. Understanding of GDPR and data governance. BI tool certifications. The BI team has historically been highly technical; you will bring the More ❯

for guidance. Strong SQL skills and understanding of data models and data principles. Experience with mobile-responsive dashboards and self-service analytics. Desirable Experience with cloud platforms (Snowflake, Azure, BigQuery). Python skills. Experience in agile delivery environments. Understanding of GDPR and data governance. BI tool certifications. The BI team has historically been highly technical; you will bring the More ❯

DevOps, integrating automated testing into a CI/CD pipeline using Jenkins or GitLab runner. Experience with either AWS, Azure OR GCP Cloud Good knowledge in GCP Storage Buckets, BigQuery, Dataflow and Cloud Functions (any Cloud). Hands-on experience with one or more programming languages (Java/JavaScript). Experience with non-functional testing using JMeter or similar More ❯

Airflow, or dbt. Strong SQL skills and experience with cloud platforms (Azure preferred). Solid programming background in Python, Scala, or Java. Knowledge of data warehousing solutions (e.g. Snowflake, BigQuery, Redshift). Strong understanding of data governance, security, and compliance (experience within financial services is a plus). Leadership experience, with the ability to mentor, influence, and set technical More ❯

Vertex AI, or similar frameworks. Implement MLOps best practices, including CI/CD for model retraining, versioning, and testing. Optimize performance and scalability of data storage solutions (e.g., Redshift, BigQuery, Snowflake, or Delta Lake). Ensure data quality, lineage, and governance through monitoring, validation, and documentation. Contribute to infrastructure-as-code (IaC) setups for reproducible deployments using Terraform, CDK More ❯

on cloud experience (AWS or GCP) with services for compute, data, and AI/ML. Proven skills in data engineering (ETL pipelines, APIs, SQL/NoSQL, data warehouses like BigQuery/Redshift). Experience with AI agents, LLMs and orchestration frameworks (LangChain, AutoGen, LlamaIndex, etc.). Demonstrated ability to ship production-ready internal tools or SaaS integrations. Strong problem More ❯

technology solutions. Strong programming skills (JavaScript, TypeScript, Python, or similar). Experience with cloud platforms (preferably Google Cloud Platform) and serverless architecture. Advanced SQL and data warehousing skills (e.g. BigQuery). Familiarity with front-end frameworks such as React. Experience with ETL/ELT processes and data visualisation tools (e.g. Looker Studio). Knowledge of AI integrations and agent More ❯

data processing frameworks (e.g., Spark, Flink). Strong experience with cloud platforms (AWS, Azure, GCP) and related data services. Hands-on experience with data warehousing tools (e.g., Snowflake, Redshift, BigQuery), Databricks running on multiple cloud platforms (AWS, Azure and GCP) and data lake technologies (e.g., S3, ADLS, HDFS). Expertise in containerization and orchestration tools like Docker and Kubernetes. More ❯

engineering with proficiency in a language such as Python for API development, Data engineering and automation tasks • A background in working with storage solutions such as PostgreSQL, MySQL, and BigQuery • Experience in API development using tools such as FastAPI or Flask, enabling data access and integration across systems • Solid knowledge of cloud platforms (GCP and/or AWS), with More ❯

Data Engineering (Spark notebooks) Synapse Data Warehouse (SQL) Fabric Data Factory pipelines Building Silver/Gold (Medallion) data models Strong SQL + Python (ideally PySpark inside Fabric) Transforming GA4 BigQuery export data Ingesting external APIs/SaaS sources (ideally Contentful or similar) Preparing Power BI-ready data models (fact/dim schemas) Strongly Preferred: Familiarity with Azure data services More ❯

SQL . Hands-on experience with data orchestration tools (Airflow, dbt, Dagster, or Prefect). Solid understanding of cloud data platforms (AWS, GCP, or Azure) and data warehousing (Snowflake, BigQuery, Redshift). Experience with streaming technologies (Kafka, Kinesis, or similar). Strong knowledge of data modelling, governance, and architecture best practices . Excellent leadership, communication, and stakeholder management skills. More ❯

healthcare dataset or similar experience, including PHI/PII handling. Familiarity with SAS and R workflows to support epidemiologists and analysts. Experience with additional SQL platforms (Postgres, Snowflake, Redshift, BigQuery). Familiarity with data quality frameworks (Great Expectations, Deequ). Experience with real-time/streaming tools (Kafka, Spark Streaming). Familiarity with big data frameworks for large-scale More ❯

technical topics for non-technical audiences. Team player - Collaborative, curious, and happy to work in a self-organising, fast-paced environment. Nice-to-Have Skills: Experience with GCP/BigQuery or other cloud data warehouses (e.g., Snowflake, Redshift). Familiarity with data orchestration tools (e.g., Airflow). Experience with data visualisation platforms (such as Preset.io/Apache Superset or More ❯