Google BigQuery

data warehouse, analytics, google cloud, olap

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1892

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1723

Google’s love letter to SQL fans who hate waiting. A serverless, fully-managed data warehouse, BigQuery excels at handling massive datasets without breaking a sweat—or requiring you to think about infrastructure. Its pay-as-you-go pricing model is straightforward enough to make Redshift sweat, and its seamless integration with the Google ecosystem (hello, Sheets and Looker) is a big plus.
But here’s the catch: it’s great for queries, not for transactions. Updates and deletes? Painfully slow. Complex transformations? Better off in a dedicated ETL tool. And while its flat-rate pricing option is tempting for high-volume users, the cost can balloon if you’re not diligent with query optimization or data partitioning.
Best suited for analytics-first shops with structured data and a love of SQL, BigQuery delivers on speed and simplicity—just don’t bring it to a transaction-heavy brawl.

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machine learning engineer Machine Learning Engineer @ rea-group AU \| 2025-12-24 REA Group promises a hands-on ML engineering role within a top-tier property brand, building scalable multi-modal AI across web and app platforms. The tech stack reads like a tour of modern ML... read more »	AI/ML, GenAI, LLM, API, Cloud Computing, AWS, GCP, Amazon SageMaker, Docker, IaC, Python, DataViz, Analytics, Data Science, SQL, PyTorch, Keras, RDBMS, MySQL, PostgreSQL, BigQuery, NoSQL, Redis, DynamoDB, ELK, Amazon EC2, S3, Terraform, CloudFormation	Machine Learning Engineer rea-group (AU) FULL TIME \| JOB LISTED REA Group promises a hands-on ML engineering role within a top-tier property brand, building scalable multi-modal AI across web and app platforms. The tech stack reads like a tour of modern ML production: Python and SQL at the core, PyTorch, Keras, Transformers and HF models for generative and vision tasks, plus XGBoost/LightGBM for scalable tabular work. You'll deploy real-time and batch pipelines across AWS or Google Cloud with Docker and IaC (Terraform or CloudFormation), and you'll touch SageMaker and Vertex AI. Data-wise, expect roles in recommender systems, property valuations, and user behavior analytics, with relational and NoSQL stores like PostgreSQL, BigQuery, Redis, DynamoDB, and ElasticSearch/Solr. The role advertises collaboration, but the breadth is daunting: multi-cloud, multi-modal, production-grade AI, plus internal-facing and external-facing AI evangelism. Salary is not disclosed, which is telling. It's a solid market outlier for ambitious ML engineers, though the hype-to-deliver ratio bears watching. Generated content Technology used AI/ML GenAI LLM API Cloud Computing AWS GCP Amazon SageMaker Docker IaC Python DataViz Analytics Data Science SQL PyTorch Keras RDBMS MySQL PostgreSQL BigQuery NoSQL Redis DynamoDB ELK Amazon EC2 S3 Terraform CloudFormation Listed At 2025-12-24 2025-11-11 (original listing) Similar Jobs Loading... Permalink View original posting
data scientist Data Science Lead - AU @ eucalyptusvc AU \| 2025-12-23 Eucalyptus, an Australian-founded digital healthcare company, seeks a Data Science Lead to steer advanced analytics, ML, and AI from scoping to production. The role blends hands-on coding with... read more »	Data Science, Analytics, AI/ML, Management, Data Engineering, MLOps, SQL, Python, Cloud Computing, GCP, BigQuery, dbt	Data Science Lead - AU eucalyptusvc (AU) FULL TIME \| JOB LISTED Eucalyptus, an Australian-founded digital healthcare company, seeks a Data Science Lead to steer advanced analytics, ML, and AI from scoping to production. The role blends hands-on coding with team leadership, demanding 7+ years in data science, at least 2 in leadership, and a track record of measurable business impact. Expect solid cloud tooling—SQL and Python, Google Cloud stack (BigQuery, Vertex AI), dbt, and production-focused ML Ops—plus a mandate to build reproducible, explainable models and data-context pipelines integrated with products. The job emphasizes cross-functional collaboration with Product and Engineering, and mentoring a team, with equity on offer and a fast, feedback-rich culture. Skeptically, the hype around patient outcomes should be tempered by regulatory, privacy, and integration realities; the market rewards practical data-to-product execution more than glossy AI promises. Overall, strong for leaders who relish operational ML at pace in healthcare. Generated content Technology used Data Science Analytics AI/ML Management Data Engineering MLOps SQL Python Cloud Computing GCP BigQuery dbt Listed At 2025-12-23 2025-09-29 (original listing) Similar Jobs Loading... Permalink View original posting
promoted Masthead Data Masthead is a data reliability platform built for Google Cloud, focused on detecting anomalies and ensuring smooth data pipeline operations. It offers real-time notifications for data issues and pipeline errors without direct access to your sensitive data.	Learn More
data engineer Director - Data Engineering @ slalom-consulting AU \| 2025-12-21 Slalom’s Director of Data Engineering reads like a tour through every enterprise cloud pattern without naming a single platform as a lasting home. It promises leadership across AWS, Azure, and... read more »	Agile/Scrum, Management, Data Engineering, AI/ML, Analytics, AWS, Azure, GCP, Cloud Computing, DWH, Data Streaming, Big Data, Spark, Presto, Amazon EMR, Redshift, Snowflake, BigQuery, Java, Python, NoSQL, DynamoDB, Cosmos, MongoDB, Kubernetes, Amazon SageMaker, Kinesis, Kafka, Tableau, Power BI, Airflow, dbt, Dagster	Director - Data Engineering slalom-consulting (AU) FULL TIME \| JOB LISTED Slalom’s Director of Data Engineering reads like a tour through every enterprise cloud pattern without naming a single platform as a lasting home. It promises leadership across AWS, Azure, and Google Cloud, steering multi‑phased data warehouse and analytics roadmaps while juggling architecture, delivery, and client pre‑sales. In practice, the role demands both hands‑on tech chops and political dexterity: building modern data platforms with Spark, Redshift, Snowflake, BigQuery, and streaming with Kafka or Kinesis, then shepherding teams through dbt, Airflow, and Dagster workflows. The market-facing pitch glosses over headcount, billing cadence, and the inevitable vendor alignment that slows momentum. Slalom’s culture—diversity, balance, growth—reads well, but the true test is delivering tangible value at scale for Global 1000 and public sector clients without turning every engagement into a platform sales cycle. Generated content Technology used Agile/Scrum Management Data Engineering AI/ML Analytics AWS Azure GCP Cloud Computing DWH Data Streaming Big Data Spark Presto Amazon EMR Redshift Snowflake BigQuery Java Python NoSQL DynamoDB Cosmos MongoDB Kubernetes Amazon SageMaker Kinesis Kafka Tableau Power BI Airflow dbt Dagster Listed At 2025-12-21 2025-11-07 (original listing) Similar Jobs Loading... Permalink View original posting

machine learning engineer Machine Learning Engineer @ rea-group AU \| 2025-12-24 REA Group promises a hands-on ML engineering role within a top-tier property brand, building scalable multi-modal AI across web and app platforms. The tech stack reads like a tour of modern ML... read more »	AI/ML, GenAI, LLM, API, Cloud Computing, AWS, GCP, Amazon SageMaker, Docker, IaC, Python, DataViz, Analytics, Data Science, SQL, PyTorch, Keras, RDBMS, MySQL, PostgreSQL, BigQuery, NoSQL, Redis, DynamoDB, ELK, Amazon EC2, S3, Terraform, CloudFormation	Machine Learning Engineer rea-group (AU) FULL TIME \| JOB LISTED REA Group promises a hands-on ML engineering role within a top-tier property brand, building scalable multi-modal AI across web and app platforms. The tech stack reads like a tour of modern ML production: Python and SQL at the core, PyTorch, Keras, Transformers and HF models for generative and vision tasks, plus XGBoost/LightGBM for scalable tabular work. You'll deploy real-time and batch pipelines across AWS or Google Cloud with Docker and IaC (Terraform or CloudFormation), and you'll touch SageMaker and Vertex AI. Data-wise, expect roles in recommender systems, property valuations, and user behavior analytics, with relational and NoSQL stores like PostgreSQL, BigQuery, Redis, DynamoDB, and ElasticSearch/Solr. The role advertises collaboration, but the breadth is daunting: multi-cloud, multi-modal, production-grade AI, plus internal-facing and external-facing AI evangelism. Salary is not disclosed, which is telling. It's a solid market outlier for ambitious ML engineers, though the hype-to-deliver ratio bears watching. Generated content Technology used AI/ML GenAI LLM API Cloud Computing AWS GCP Amazon SageMaker Docker IaC Python DataViz Analytics Data Science SQL PyTorch Keras RDBMS MySQL PostgreSQL BigQuery NoSQL Redis DynamoDB ELK Amazon EC2 S3 Terraform CloudFormation Listed At 2025-12-24 2025-11-11 (original listing) Similar Jobs Loading... Permalink View original posting
data scientist Data Science Lead - AU @ eucalyptusvc AU \| 2025-12-23 Eucalyptus, an Australian-founded digital healthcare company, seeks a Data Science Lead to steer advanced analytics, ML, and AI from scoping to production. The role blends hands-on coding with... read more »	Data Science, Analytics, AI/ML, Management, Data Engineering, MLOps, SQL, Python, Cloud Computing, GCP, BigQuery, dbt	Data Science Lead - AU eucalyptusvc (AU) FULL TIME \| JOB LISTED Eucalyptus, an Australian-founded digital healthcare company, seeks a Data Science Lead to steer advanced analytics, ML, and AI from scoping to production. The role blends hands-on coding with team leadership, demanding 7+ years in data science, at least 2 in leadership, and a track record of measurable business impact. Expect solid cloud tooling—SQL and Python, Google Cloud stack (BigQuery, Vertex AI), dbt, and production-focused ML Ops—plus a mandate to build reproducible, explainable models and data-context pipelines integrated with products. The job emphasizes cross-functional collaboration with Product and Engineering, and mentoring a team, with equity on offer and a fast, feedback-rich culture. Skeptically, the hype around patient outcomes should be tempered by regulatory, privacy, and integration realities; the market rewards practical data-to-product execution more than glossy AI promises. Overall, strong for leaders who relish operational ML at pace in healthcare. Generated content Technology used Data Science Analytics AI/ML Management Data Engineering MLOps SQL Python Cloud Computing GCP BigQuery dbt Listed At 2025-12-23 2025-09-29 (original listing) Similar Jobs Loading... Permalink View original posting
promoted Masthead Data Masthead is a data reliability platform built for Google Cloud, focused on detecting anomalies and ensuring smooth data pipeline operations. It offers real-time notifications for data issues and pipeline errors without direct access to your sensitive data.	Learn More
data engineer Director - Data Engineering @ slalom-consulting AU \| 2025-12-21 Slalom’s Director of Data Engineering reads like a tour through every enterprise cloud pattern without naming a single platform as a lasting home. It promises leadership across AWS, Azure, and... read more »	Agile/Scrum, Management, Data Engineering, AI/ML, Analytics, AWS, Azure, GCP, Cloud Computing, DWH, Data Streaming, Big Data, Spark, Presto, Amazon EMR, Redshift, Snowflake, BigQuery, Java, Python, NoSQL, DynamoDB, Cosmos, MongoDB, Kubernetes, Amazon SageMaker, Kinesis, Kafka, Tableau, Power BI, Airflow, dbt, Dagster	Director - Data Engineering slalom-consulting (AU) FULL TIME \| JOB LISTED Slalom’s Director of Data Engineering reads like a tour through every enterprise cloud pattern without naming a single platform as a lasting home. It promises leadership across AWS, Azure, and Google Cloud, steering multi‑phased data warehouse and analytics roadmaps while juggling architecture, delivery, and client pre‑sales. In practice, the role demands both hands‑on tech chops and political dexterity: building modern data platforms with Spark, Redshift, Snowflake, BigQuery, and streaming with Kafka or Kinesis, then shepherding teams through dbt, Airflow, and Dagster workflows. The market-facing pitch glosses over headcount, billing cadence, and the inevitable vendor alignment that slows momentum. Slalom’s culture—diversity, balance, growth—reads well, but the true test is delivering tangible value at scale for Global 1000 and public sector clients without turning every engagement into a platform sales cycle. Generated content Technology used Agile/Scrum Management Data Engineering AI/ML Analytics AWS Azure GCP Cloud Computing DWH Data Streaming Big Data Spark Presto Amazon EMR Redshift Snowflake BigQuery Java Python NoSQL DynamoDB Cosmos MongoDB Kubernetes Amazon SageMaker Kinesis Kafka Tableau Power BI Airflow dbt Dagster Listed At 2025-12-21 2025-11-07 (original listing) Similar Jobs Loading... Permalink View original posting

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Machine Learning Engineer @ rea-group

Data Science Lead - AU @ eucalyptusvc

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Director - Data Engineering @ slalom-consulting