76 to 100 of 1,034 Remote BigQuery Jobs

procurement. Communication & Stakeholder Management : Ability to translate technical concepts for non-technical stakeholders; strong leadership and mentoring skills. Performance Analytics : Experience with Google Analytics, BigQuery, Looker Studio, Tag Manager. Domain expertise in benefits or civic services; familiarity with public-sector frameworks like SIFA. Security clearance (BPSS, SC, or DV More ❯

and empower your team members to grow their skills and performance. You have experience using cloud based analytical platforms such as Databricks, Snowflake, Google BigQuery and the like. You can leverage the power and scalability of these platforms to handle large and complex data sets. Experience of marketing campaign More ❯

s greatest challenges: affordable care. What you’ll need Mastery of SQL with experience developing data pipelines in a cloud based database environment (e.g. BigQuery). 3+ years experience delivering data products in a modern BI technology (ideally Looker) or open source data frameworks (e.g. streamlit). Experience using More ❯

with Python, SQL, and modern ETL tools (e.g., Airflow, dbt) Solid grasp of cloud platforms (AWS/GCP/Azure) and data warehouses (e.g., BigQuery, Snowflake) Familiarity with streaming technologies (Kafka, Kinesis, etc.) Passion for clean, maintainable code and robust data systems Previous experience in a fintech or regulated More ❯

with Python, SQL, and modern ETL tools (e.g., Airflow, dbt) Solid grasp of cloud platforms (AWS/GCP/Azure) and data warehouses (e.g., BigQuery, Snowflake) Familiarity with streaming technologies (Kafka, Kinesis, etc.) Passion for clean, maintainable code and robust data systems Previous experience in a fintech or regulated More ❯

data warehousing. Experience with cloud platforms (e.g., AWS, Azure, GCP) and data lake/data mesh architectures. Familiarity with modern data tools (e.g., Snowflake, BigQuery, dbt, Apache Kafka, Talend, etc.). Strong understanding of data security, privacy regulations, and best practices. Excellent communication and stakeholder management skills. Ability to More ❯

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 More ❯

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 More ❯

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 More ❯

strong focus on Data work. • Strong proficiency in leading big data technologies (e.g., Hadoop, Spark, Hive). • Familiarity with data warehousing solutions (e.g., Redshift, BigQuery, Snowflake). • Strong problem-solving skills and attention to detail. • Excellent communication and collaboration skills. Bonus • Experience working across the complete data stack. • Experience More ❯

strong focus on Data work. • Strong proficiency in leading big data technologies (e.g., Hadoop, Spark, Hive). • Familiarity with data warehousing solutions (e.g., Redshift, BigQuery, Snowflake). • Strong problem-solving skills and attention to detail. • Excellent communication and collaboration skills. Bonus • Experience working across the complete data stack. • Experience More ❯

while mentoring and coaching others to succeed. Have a strong background in building and managing data infrastructure at scale, with expertise in Python, SQL, BigQuery, AWS, dbt and Airflow. Have a strong background in data modelling and building scalable data pipelines. Are naturally curious and enthusiastic about experimenting with More ❯

mid-level engineers through their development journey while fostering a culture of continuous learning and growth. Must Have: Base de Datos: PostgreSQL, MySQL, Snowflake, BigQuery MLOps: MLflow, TensorFlow, PyTorch, Scikit-learn. Cloud Expertise: Familiar with Kubernetes, Microservices, REST, OpenAPI, AWS, Docker, Containers, Terraform, CI/CD, Prometheus, Grafana, IaC More ❯

Extensive experience as a BI Developer/Analytics Engineer, specialising in Looker (dashboarding, advanced LookML). Strong SQL proficiency with cloud data warehouses (e.g., BigQuery ). Solid understanding of data warehousing and modelling. Proven background in marketing data and analytics (e.g., campaign performance, web analytics). Experience translating business More ❯

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 More ❯

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 More ❯

data services (S3, Athena, Glue) Experience with Airflow for scheduling and orchestrating workflows Experience working with data lakes or modern data warehouses (Snowflake, Redshift, BigQuery) A pragmatic problem solver who can balance technical excellence with business needs At Funding Circle we are committed to building diverse teams so please More ❯

AWS, Azure, GCP), while also gaining opportunities to learn about and use data services such as Databricks, Data Factory, Synapse, Kafka, Redshift, Glue, Athena, BigQuery, S3, Cloud Data Fusion etc. Responsibilities You're an engineer at heart and enjoy the challenge of building reliable, efficient data applications systems, services More ❯

Understanding of data engineering principles, ETL/ELT processes, and technologies like Apache Kafka, Spark, or Airflow. Familiarity with data storage systems (e.g., Snowflake, BigQuery, Redshift) and cloud platforms (e.g., AWS, Azure, GCP). Comfort building software that processes billions of transactions or data elements. Strong problem-solving skills More ❯

in software and data engineering, programming languages (python, java etc.). Understanding of orchestration (Composer, DAGs), data processing (DataFlow, dbt), and database capabilities (e.g. BigQuery, CloudSQL, BigTable). Knowledge of container technologies (Docker, Kubernetes), IaaC (Terraform) and experience with cloud platforms such as GCP. Detailed understanding of automated CI More ❯

in software and data engineering, programming languages (python, java etc.). Understanding of orchestration (Composer, DAGs), data processing (DataFlow, dbt), and database capabilities (e.g. BigQuery, CloudSQL, BigTable). Knowledge of container technologies (Docker, Kubernetes), IaaC (Terraform) and experience with cloud platforms such as GCP. Detailed understanding of automated CI More ❯

equivalent, with Collibra and Collibra APIs or GCP SDK experience You are recognized for your understanding of and experience with Oracle, SQL server, GCP BigQuery,PostgreSQL,and NoSQL You are an expert communicator and strategic thinker, able to provide a consultative approach in alignment with the Telco Management Industry More ❯

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 More ❯

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 More ❯

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 More ❯