51 to 75 of 304 Permanent BigQuery Jobs

similar area 5+ years of experience working as a professional software engineer, data in industry Expertise with Python coding and type system Expertise in writing SQL (GQL, PostgreSQL, and BigQuery are a plus) Experience with building both batch and streaming ETL pipelines using data processing engines Deep understanding of building Knowledge Graphs entailing biological ontologies, and leveraging graph DBs More ❯

minimal disruption to business operations. Optimize data storage and retrieval mechanisms across cloud-based databases, preferably Azure CosmosDB, Neo4j Graph DB (or similar technology e.g., Amazon RDS, Azure SQL, BigQuery, NoSQL). Application Architecture & Security Architect microservices-based applications, ensuring modular, scalable, and API-first designs Design and implement application security controls, including IAM, Zero Trust models, encryption, and More ❯

CD pipelines and infrastructure as code (Terraform) for rapid deployment. Experience that will give you an edge Experience using Python on Google Cloud Platform for Big Data projects, including BigQuery, DataFlow (Apache Beam), Cloud Run, Cloud Functions, Cloud Workflows, and Cloud Composer. Strong SQL development skills. Proven expertise in data modeling, ETL development, and data warehousing. Knowledge of data More ❯

and database design skills, with proficiency in dbt/Dataform or similar SQL development frameworks Proficient with cloud-based modern data warehousing technologies, particularly GCP and related technologies, especially BigQuery (we are also open to considering candidates with strong comparable experience on other leading cloud platforms) Strong understanding of best practices and trends in data, software engineering and AI More ❯

and database design skills, with proficiency in dbt/Dataform or similar SQL development frameworks Proficient with cloud-based modern data warehousing technologies, particularly GCP and related technologies, especially BigQuery (we are also open to considering candidates with strong comparable experience on other leading cloud platforms) Strong understanding of best practices and trends in data, software engineering and AI More ❯

experience of people management or desire to manage individuals on the team Nice to Have Experience with some of these- Kafka, Kinesis, Kinesis Analytics, Glue, Lambda, Kubernetes, ETL pipelines, BigQuery, Dataflow, BigTable, and SQL Enthusiastic about learning and applying new technologies (growth mindset). Ability to build new solutions and support our data solutions/products. What's in More ❯

share documentation, and support technical best practices Integrate infrastructure and data services across cloud platforms Skills and Experience Expertise in cloud platforms: Azure : Data Factory, Synapse, Monitor, ARM GCP : BigQuery, Dataflow, Cloud Composer, Pub/Sub Strong knowledge of data warehousing, storage, and modelling Experience with ETL/ELT processes and performance tuning Hands-on scripting (Python, PowerShell) for More ❯

share documentation, and support technical best practices Integrate infrastructure and data services across cloud platforms Skills and Experience Expertise in cloud platforms: Azure : Data Factory, Synapse, Monitor, ARM GCP : BigQuery, Dataflow, Cloud Composer, Pub/Sub Strong knowledge of data warehousing, storage, and modelling Experience with ETL/ELT processes and performance tuning Hands-on scripting (Python, PowerShell) for More ❯

in ETL tools like Informatica Glue Databricks and DataProc with strong coding skills in Python PySpark and SQL. You will have expertise in data warehousing solutions such as Snowflake BigQuery Lakehouse and Delta Lake is essential including the ability to calculate processing costs and address performance issues. A solid understanding of DevOps and infrastructure needs is also required. Job More ❯

communications both internally and with external clients. Strong hands-on experience using SQL for multi-step/complex analytics is essential for this role. Experience in cloud platforms (GCP – BigQuery, Azure -Synapse, Snowflake) and exposure to data science tools/languages such as Python, dbt, D3, Github, GCP/AWS would be advantageous. (This is not a technical advanced More ❯

communications both internally and with external clients. Strong hands-on experience using SQL for multi-step/complex analytics is essential for this role. Experience in cloud platforms (GCP – BigQuery, Azure -Synapse, Snowflake) and exposure to data science tools/languages such as Python, dbt, D3, Github, GCP/AWS would be advantageous. (This is not a technical advanced More ❯

years experience in a similar role. Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF Designing Databricks based solutions for Azure/AWS, Jenkins, Terraform, StackDriver More ❯

and storage solutions in cloud environments (AWS, Azure, GCP) - Writing complex queries against relational and non-relational databases - Leading or contributing to key projects involving technologies like Databricks, Snowflake, BigQuery and Fabric - Applying software engineering best practices to data engineering, including CI/CD, monitoring and alerting - Collaborating with cross-functional teams including Data Scientists, Architects and Analysts - Mentoring More ❯

a challenging start-up environment. You have a curious mind and love problem-solving. We are looking for candidates who have Demonstrable, in-depth experience with SQL, particularly in BigQuery and PostgreSQL. Proven experience with dbt, focusing on building and maintaining efficient, scalable, and reliable DAGs. Proficiency in Python for data manipulation, scripting, or automation tasks. Are proficient with More ❯

libraries (e.g.scikit-learn, pandas, NumPy, SciPy, etc) Experience with ML frameworks such as TensorFlow, PyTorch, XGBoost, LightGBM, or similar Strong SQL skills and experience with data warehousing solutions (Snowflake, BigQuery, Redshift) Experience with cloud platforms (AWS, Azure, GCP) and their ML and AI services (SageMaker, Azure ML, Vertex AI) Knowledge of MLOps tools including Docker, MLflow, Kubeflow, or similar More ❯

Demonstrable experience deploying machine learning solutions in a production environment, and familiarity with version controls systems (e.g. Git) Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to More ❯

Demonstrable experience deploying machine learning solutions in a production environment, and familiarity with version controls systems (e.g. Git) Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to More ❯

Demonstrable experience deploying machine learning solutions in a production environment, and familiarity with version controls systems (e.g. Git) Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to More ❯

Studio), preferably within a marketing or media environment Understanding of digital media metrics (e.g., impressions, clicks, conversions, reach, frequency, CTR, CPM, ROAS) Proficient in SQL, with working knowledge of BigQuery or other cloud-based databases Familiarity with Python or R for data manipulation or statistical analysis Knowledge of advertising technology, campaign tracking, and data integration tools is a plus More ❯

ll need Extensive experience leading engineering teams in cloud-based data platforms, preferably with GCP expertise. Deep knowledge of cloud architecture, data engineering, pipelines, and big data technologies (e.g., BigQuery, Dataflow, Pub/Sub). Proficiency in Python, Java, or Scala; familiarity with microservices, Docker, Kubernetes, CI/CD tools (e.g., Jenkins, GitLab CI), and cloud monitoring. Proven experience More ❯

ll need Extensive experience leading engineering teams in cloud-based data platforms, preferably with GCP expertise. Deep knowledge of cloud architecture, data engineering, pipelines, and big data technologies (e.g., BigQuery, Dataflow, Pub/Sub). Proficiency in Python, Java, or Scala; familiarity with microservices, Docker, Kubernetes, CI/CD tools (e.g., Jenkins, GitLab CI), and cloud monitoring. Proven experience More ❯

data solutions Migrating from Azure to GCP Automate data lifecycle processes and optimise cloud resource usage Support analytics and self-service reporting initiatives Skills & Experience Strong experience with GCP, BigQuery, Dataflow Proficiency in Python and Terraform Skilled in ETL/ELT, data modelling, and metadata management Familiarity with CI/CD, DevOps, and Infrastructure-as-Code Knowledge of insurance More ❯

data solutions Migrating from Azure to GCP Automate data lifecycle processes and optimise cloud resource usage Support analytics and self-service reporting initiatives Skills & Experience Strong experience with GCP, BigQuery, Dataflow Proficiency in Python and Terraform Skilled in ETL/ELT, data modelling, and metadata management Familiarity with CI/CD, DevOps, and Infrastructure-as-Code Knowledge of insurance More ❯

relational/non-relational databases. Proficiency in Python and/or Java for data services and API integration. Proven experience with cloud platforms (GCP preferred) and data warehouses like BigQuery or Snowflake. Strong analytical skills and experience working with large, complex datasets. Excellent communication and project management abilities. 5+ years in data engineering, ideally within fast-paced, content-driven More ❯

relational/non-relational databases. Proficiency in Python and/or Java for data services and API integration. Proven experience with cloud platforms (GCP preferred) and data warehouses like BigQuery or Snowflake. Strong analytical skills and experience working with large, complex datasets. Excellent communication and project management abilities. 5+ years in data engineering, ideally within fast-paced, content-driven More ❯