51 to 75 of 311 BigQuery Jobs

Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/or implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps: Git, Docker, Jenkins/ More ❯

Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/or implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps: Git, Docker, Jenkins/ More ❯

DBT, Airflow, Matillion, Fivetran, or Informatica. Establish architecture blueprints for multi-region, multi-tenant, and secure Snowflake deployments. Lead migration from legacy data warehouses (Teradata, Oracle, SQL Server, Redshift, BigQuery, etc.) to Snowflake. Qualifications we seek in you! Minimum qualifications Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field . Preferred qualifications BE/ More ❯

DBT, Airflow, Matillion, Fivetran, or Informatica. Establish architecture blueprints for multi-region, multi-tenant, and secure Snowflake deployments. Lead migration from legacy data warehouses (Teradata, Oracle, SQL Server, Redshift, BigQuery, etc.) to Snowflake. Qualifications we seek in you! Minimum qualifications Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field . Preferred qualifications BE/ More ❯

Experience using SQL and Python to effectively automate data pipelines and other tasks with tools such as dbt, airflow. Strong experience with data lakehouse architecture (e.g DataBricks,Redshift, Snowflake, BigQuery). Exposure to cloud services and their configuration (e.g AWS). Experience in building and documenting data architectures and ETL/ELT processes, with a strong emphasis on performance More ❯

Skills : Advanced hands-on experience with major cloud platforms (Azure, AWS, GCP), including cloud-native data services, orchestration, monitoring, and automation. Proven experience in GCP-based data platforms , including BigQuery, Dataflow, CloudSQL, Spanner, Pub Sub, Cloud composer and GKE. Data Engineering : Proficient in modern data tools and frameworks for building, operating, and optimising ETL/ELT pipelines, streaming data More ❯

with openness to various data platforms including AWS, Azure, and Google Cloud. Strong knowledge of data services across multiple platforms (e.g., AWS S3, Redshift, Glue, Azure Blob Storage, Google BigQuery). Expertise in data modelling (Dimensional, Data Vault, Enterprise). Experience designing and implementing modern data architectures. Proficiency with integration/orchestration tools (Airflow, dbt, Glue). Strong communication More ❯

investors and the Board Technology Background of the CTO: · Languages: Python, TypeScript/JavaScript (Node.js), Dart (Flutter), SQL/MySQL, JSON, REST, GraphQL · Cloud and Data: Google Cloud Platform (BigQuery, Cloud Run, Firestore, Pub/Sub) · DevOps and Tooling: GitHub, GitHub Actions, Terraform, Docker, Kubernetes · Monitoring: Stackdriver, Grafana, Prometheus · Security: OAuth2, SSO, IAM, ISO27001 alignment, penetration testing · Analytics and More ❯

ETL frameworks, particularly Apache Airflow (3+ years) Strong understanding of CI/CD, Infrastructure as Code (Terraform), and containerization Experience designing and optimizing big data processing systems particularly using Bigquery/GCP Leadership & Communication Exceptional leadership abilities with proven success developing technical teams Outstanding communication skills for both technical and commercial audiences Ability to operate effectively at both strategic More ❯

focus on backend technologies and building distributed services. Proficiency in one or more programming languages including Java, Python, Scala or Golang. Experience with columnar, analytical cloud data warehouses (e.g., BigQuery, Snowflake, Redshift) and data processing frameworks like Apache Spark is essential. Experience with cloud platforms like AWS, Azure, or Google Cloud. Strong proficiency in designing, developing, and deploying microservices 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 ❯

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 ❯

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 ❯

/Java) and SQL Deep experience with data pipeline orchestration tools (Airflow, dbt, Dagster, Prefect) Strong knowledge of cloud data platforms (AWS, GCP, or Azure) and data warehousing (Snowflake, BigQuery, Redshift) Hands-on experience with streaming technologies (Kafka, Kinesis, or similar) Solid understanding of data modelling, governance, and architecture best practices Familiarity with machine learning pipelines or AI model More ❯

/Java) and SQL Deep experience with data pipeline orchestration tools (Airflow, dbt, Dagster, Prefect) Strong knowledge of cloud data platforms (AWS, GCP, or Azure) and data warehousing (Snowflake, BigQuery, Redshift) Hands-on experience with streaming technologies (Kafka, Kinesis, or similar) Solid understanding of data modelling, governance, and architecture best practices Familiarity with machine learning pipelines or AI model More ❯

and optimize data pipelines and workflows using modern tools (e.g., dbt, Airflow, SQL, Python). Take ownership of large-scale analytics platforms and data warehouse solutions (such as Snowflake, BigQuery, Redshift). Mentor and guide engineers across analytics and data engineering disciplines. Ensure solutions adhere to best practices for data governance, integrity, and scalability. Drive continuous innovation in data More ❯

and optimize data pipelines and workflows using modern tools (e.g., dbt, Airflow, SQL, Python). Take ownership of large-scale analytics platforms and data warehouse solutions (such as Snowflake, BigQuery, Redshift). Mentor and guide engineers across analytics and data engineering disciplines. Ensure solutions adhere to best practices for data governance, integrity, and scalability. Drive continuous innovation in data More ❯

reinforcement learning, LLM orchestration, RAG systems, etc Familiarity with cloud services and MLOps tooling to deploy and scale data and ML workloads cost-effectively Familiarity with data warehouses (Redshift, BigQuery, Snowflake, etc) and best practices around data pipeline tools Strong proficiency in SQL Comfort with ambiguity and short feedback loops A passion for building products that make a real More ❯

experience with data modeling tools such as Erwin, ER/Studio, SqlDBM or SQL DB-native modelling tools. Hands-on experience with cloud data platforms (Azure Synapse, Snowflake, GCP BigQuery) and modern data storage solutions. Strong SQL skills and good knowledge of data warehousing, lakehouses, and OLTP/OLAP systems. Demonstratable interest and awareness in emerging technologies What we More ❯

and data engineering stack, including Airflow, Vertex AI, Kubernetes, Docker, GitHub Actions, Jenkins, Google Cloudbuild, Prometheus, and Grafana. Solid experience in cloud data storage , with particular expertise in Google BigQuery (GBQ), GCS/S3 Demonstrable ability to produce high-quality engineering solutions free of technical debt, with a passion for maintaining high standards. An excellent team player , capable of More ❯

Experience Masters degree level Exposure to working with digital analytics tools (e.g. Google Analytics or Adobe Analytics) Knowledge of coding language or modelling tools relevant to data manipulation (e.g. BigQuery, SQL, R, Python, MatLab, Stata) Knowledge of dashboarding solutions (e.g. Power BI, Looker, Tableau) If this sounds like you, please get in touch! We look forward to meeting you. More ❯

welcome but not essential. Understanding of digital performance metrics and data connectors (experience with platforms like Google Ads, Meta, or DSPs a bonus). Familiarity with large datasets (e.g. BigQuery, Snowflake, or other cloud platforms). Strong communication skills and a problem-solving mindset. What’s on offer Salary in the region of £60–75K plus equity participation. Direct More ❯

welcome but not essential. Understanding of digital performance metrics and data connectors (experience with platforms like Google Ads, Meta, or DSPs a bonus). Familiarity with large datasets (e.g. BigQuery, Snowflake, or other cloud platforms). Strong communication skills and a problem-solving mindset. What’s on offer Salary in the region of £60–75K plus equity participation. Direct 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 ❯

and lineage. Drive CI/CD practices using GitHub Actions or similar tools. Collaborate with cross-functional teams to improve platform capabilities and analytics maturity. Requirements: Proven experience in BigQuery and dbt/dataform for data warehousing and transformation. Strong SQL skills and understanding of modern data architecture principles. Hands-on experience with Tableau for enterprise-grade dashboard development. More ❯