1 to 25 of 183 Remote BigQuery Jobs

Proficiency in Python for data transformation, automation, and integration tasks, and SQL for building and optimising complex queries. Hands-on experience with cloud data platforms, ideally Google Cloud Platform (BigQuery, Cloud Storage, Cloud Functions) or equivalents such as AWS Redshift or Azure Synapse. Practical experience using modern data tooling such as DBT, Airflow, or Prefect for orchestration, transformation, and 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. About You As much as we love working with great, fun people, there are More ❯

various database management system skills. a good understanding of different database types, designs, and data modelling systems. experience with cloud platforms like AWS and GCP, including services such as BigQuery, RDS, and Athena. familiarity with Tableau and project management tools like and Notion. knowledge of APIs from music Digital Service Providers (e.g., Spotify, Apple Music). previous experience at 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 ❯

/ELT pipelines using any major programming language, with a strong preference for Python · Databases & SQL: Extensive experience working with databases, SQL, and data warehouses. Familiarity with Postgres and BigQuery required. · Data Ingestion: Experience ingesting and processing data from diverse sources (databases, data warehouses, and external APIs) · Infrastructure-as-Code (IaC): Hands-on experience with an IaC solution, such 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 ❯

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 ❯

product development. Translate business requirements into scalable technical solutions that support critical client outcomes. Analytics Engineering Leaders: Architect and optimise data pipelines, ELT workflows, and cloud warehouse platforms (Snowflake, BigQuery, Redshift). Lead teams working with dbt, SQL, Python, and Airflow to drive data transformation at scale. Ensure data governance, quality, and modelling standards are upheld across solutions. Work 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 ❯

pipelines Automating and orchestrating workflows using tools such as AWS Glue, Azure Data Factory or Google Cloud Dataflow Working with leading data platforms like Amazon S3, Azure Synapse, Google BigQuery and Snowflake Implementing Lakehouse architectures using Databricks or Snowflake Collaborating with engineers, analysts and client teams to deliver value-focused data solutions What We’re Looking For: Strong experience More ❯

strategy definition, vendor assessment, and governance adoption. Experience establishing reference data management and data quality practices at enterprise scale. Knowledge of analytical data architectures: data lakes, warehouses (e.g., Snowflake, BigQuery), BI/reporting, and ETL pipelines. Proficiency in public cloud platforms (AWS, Google Cloud Platform, Microsoft Azure). Experience with both transactional RDBMS and modern distributed/cloud-native More ❯

strategy definition, vendor assessment, and governance adoption. Experience establishing reference data management and data quality practices at enterprise scale. Knowledge of analytical data architectures: data lakes, warehouses (e.g., Snowflake, BigQuery), BI/reporting, and ETL pipelines. Proficiency in public cloud platforms (AWS, Google Cloud Platform, Microsoft Azure). Experience with both transactional RDBMS and modern distributed/cloud-native More ❯

strategy definition, vendor assessment, and governance adoption. Experience establishing reference data management and data quality practices at enterprise scale. Knowledge of analytical data architectures: data lakes, warehouses (e.g., Snowflake, BigQuery), BI/reporting, and ETL pipelines. Proficiency in public cloud platforms (AWS, Google Cloud Platform, Microsoft Azure). Experience with both transactional RDBMS and modern distributed/cloud-native More ❯

strategy definition, vendor assessment, and governance adoption. Experience establishing reference data management and data quality practices at enterprise scale. Knowledge of analytical data architectures: data lakes, warehouses (e.g., Snowflake, BigQuery), BI/reporting, and ETL pipelines. Proficiency in public cloud platforms (AWS, Google Cloud Platform, Microsoft Azure). Experience with both transactional RDBMS and modern distributed/cloud-native More ❯

strategy definition, vendor assessment, and governance adoption. Experience establishing reference data management and data quality practices at enterprise scale. Knowledge of analytical data architectures: data lakes, warehouses (e.g., Snowflake, BigQuery), BI/reporting, and ETL pipelines. Proficiency in public cloud platforms (AWS, Google Cloud Platform, Microsoft Azure). Experience with both transactional RDBMS and modern distributed/cloud-native More ❯

functional teams and communicating with both technical and non-technical stakeholders. Curious, collaborative, and impact-driven — you enjoy turning data into action. Experience working with cloud-based data environments (BigQuery, GCP); exposure to dbt or Dataform is a plus. Experience with Python is desirable. This is a 6 month contract. It is a hybrid role, based in central London More ❯

environment. About You Highly proficient in SQL and Python . Experience with data modelling (3NF, Kimball) and modern data integration tools. Exposure to cloud-based platforms such as Snowflake , BigQuery , or similar is advantageous. Experience with DBT , Airbyte , or APIs is desirable. Strong communicator who can link data initiatives to commercial outcomes. Enjoys mentoring, providing direction, and developing others More ❯

environment. About You Highly proficient in SQL and Python . Experience with data modelling (3NF, Kimball) and modern data integration tools. Exposure to cloud-based platforms such as Snowflake , BigQuery , or similar is advantageous. Experience with DBT , Airbyte , or APIs is desirable. Strong communicator who can link data initiatives to commercial outcomes. Enjoys mentoring, providing direction, and developing others More ❯