1 to 25 of 32 Permanent Amazon Athena Jobs in England

Job ID: Amazon Web Services Australia Pty Ltd Are you a Senior Cloud Architect with GenAI consulting specialist? Do you have real-time Data Analytics, Data Warehousing, Big Data, Modern Data Strategy, Data Lake, Data Engineering and GenAI experience? Do you have senior stakeholder engagement experience to support pre-sales and deliver consulting engagements? Do you like to solve … Vetting Agency clearance (see ). Key job responsibilities Expertise: Collaborate with pre-sales and delivery teams to help partners and customers learn and use services such as AWS Glue, Amazon S3, Amazon DynamoDB, Amazon Relational Database Service (RDS), Amazon Elastic Map Reduce (EMR), Amazon Kinesis, Amazon Redshift, Amazon Athena, AWS Lake Formation … Amazon DataZone, Amazon SageMaker, Amazon Quicksight and Amazon Bedrock. Solutions: Support pre-sales and deliver technical engagements with partners and customers. This includes participating in pre-sales visits, understanding customer requirements, creating consulting proposals and creating packaged data analytics service offerings. Delivery: Engagements include projects proving the use of AWS services to support new distributed computing More ❯

AWS, Kafka, Spark, Flink, or Beam, especially deployment and monitoring Have productized ML research projects Are familiar with Airflow, Kubernetes, data lake systems, and file formats like Parquet, Orc, Athena Possess relevant AWS or Kafka certifications Enjoy working in a diverse, innovative environment Are motivated by collaboration, learning, and exploring new tools Value company ownership and responsible business practices More ❯

deployment strategies. Solid knowledge of infrastructure as code using AWS CloudFormation and Terraform to automate and manage cloud resources. Experience developing ETL workflows using AWS Glue, querying data with Athena, and managing access and governance with Lake Formation. Strong command of AWS Lambda for serverless data processing and Boto3 for programmatic interaction with AWS services. Demonstrated experience working with More ❯

deployment strategies. Solid knowledge of infrastructure as code using AWS CloudFormation and Terraform to automate and manage cloud resources. Experience developing ETL workflows using AWS Glue, querying data with Athena, and managing access and governance with Lake Formation. Strong command of AWS Lambda for serverless data processing and Boto3 for programmatic interaction with AWS services. Demonstrated experience working with More ❯

deployment strategies. Solid knowledge of infrastructure as code using AWS CloudFormation and Terraform to automate and manage cloud resources. Experience developing ETL workflows using AWS Glue, querying data with Athena, and managing access and governance with Lake Formation. Strong command of AWS Lambda for serverless data processing and Boto3 for programmatic interaction with AWS services. Demonstrated experience working with More ❯

deployment strategies. Solid knowledge of infrastructure as code using AWS CloudFormation and Terraform to automate and manage cloud resources. Experience developing ETL workflows using AWS Glue, querying data with Athena, and managing access and governance with Lake Formation. Strong command of AWS Lambda for serverless data processing and Boto3 for programmatic interaction with AWS services. Demonstrated experience working with More ❯

deployment strategies. Solid knowledge of infrastructure as code using AWS CloudFormation and Terraform to automate and manage cloud resources. Experience developing ETL workflows using AWS Glue, querying data with Athena, and managing access and governance with Lake Formation. Strong command of AWS Lambda for serverless data processing and Boto3 for programmatic interaction with AWS services. Demonstrated experience working with More ❯

and logging data visualisation : ability to build interactive dashboards and reports using tools such as Plotly, Dash, Matplotlib or Streamlit cloud and tooling : experience with AWS (S3, Lambda, Bedrock, Athena, or SNS), or other cloud services Azure, or GCP; and familiarity with version control (Git/GitHub), command line, and IDEs software engineering practices : unit testing (e.g. pytest), code More ❯

and logging data visualisation : ability to build interactive dashboards and reports using tools such as Plotly, Dash, Matplotlib or Streamlit cloud and tooling : experience with AWS (S3, Lambda, Bedrock, Athena, or SNS), or other cloud services Azure, or GCP; and familiarity with version control (Git/GitHub), command line, and IDEs software engineering practices : unit testing (e.g. pytest), code More ❯

and logging data visualisation : ability to build interactive dashboards and reports using tools such as Plotly, Dash, Matplotlib or Streamlit cloud and tooling : experience with AWS (S3, Lambda, Bedrock, Athena, or SNS), or other cloud services Azure, or GCP; and familiarity with version control (Git/GitHub), command line, and IDEs software engineering practices : unit testing (e.g. pytest), code More ❯

Hands-on experience with cloud platforms (preferably AWS or Snowflake) and ETL/ELT orchestration tools (e.g. Airflow, dbt). Desirable Skills Familiarity with tools such as MongoDB , Glue , Athena , and React . Experience in API development and working with modern data infrastructure. Ability to work independently, solve complex problems, and contribute ideas proactively. Working Environment Hybrid working model More ❯

Hands-on experience with cloud platforms (preferably AWS or Snowflake) and ETL/ELT orchestration tools (e.g. Airflow, dbt). Desirable Skills Familiarity with tools such as MongoDB , Glue , Athena , and React . Experience in API development and working with modern data infrastructure. Ability to work independently, solve complex problems, and contribute ideas proactively. Working Environment Hybrid working model More ❯

Site Reliability Engineering, or Infrastructure roles. Strong experience with public cloud environments, particularly AWS (e.g., EC2, S3, RDS, IAM, EKS). Familiarity with AWS ETL services (e.g., Glue Jobs, Athena, Firehose). Experience with AWS migration tools (e.g., DMS, DataSync). Ability to manage AWS Organizations, accounts, and permission sets. Hands-on experience with Infrastructure-as-Code tools (e.g. More ❯

Drive innovation through advanced analytics and research-based problem solving. To be successful you should have: 10 years hands-on experience in AWS data engineering technologies, including Glue, PySpark, Athena, Iceberg, Databricks, Lake Formation, and other standard data engineering tools. Previous experience in implementing best practices for data engineering, including data governance, data quality, and data security. Proficiency in More ❯

Drive innovation through advanced analytics and research-based problem solving. To be successful you should have: 10 years hands-on experience in AWS data engineering technologies, including Glue, PySpark, Athena, Iceberg, Databricks, Lake Formation, and other standard data engineering tools. Previous experience in implementing best practices for data engineering, including data governance, data quality, and data security. Proficiency in More ❯

reliability in the organization Qualifications Understanding of data engineering (including SQL , Python , Data Warehousing , ETL , Dimensional Modelling , Analytics ) Understanding of cloud data infrastructure elements, and ideally AWS (Redshift, Glue, Athena, S3) and understanding of existing governance frameworks of data quality and their dimensions (DAMA, GOV.UK, etc.) Experience in Exploratory Testing, automation experience, and time and attention management between multiple More ❯

and PySpark for data processing and automation. Strong command of SQL for data querying, transformation, and performance tuning. Deep experience with cloud platforms , preferably AWS (e.g., S3, Glue, Redshift, Athena, EMR, Lambda). Experience with Azure or GCP is a plus. Experience building and managing data lakes and data warehouses. Strong understanding of distributed systems and big data processing. More ❯

and PySpark for data processing and automation. Strong command of SQL for data querying, transformation, and performance tuning. Deep experience with cloud platforms , preferably AWS (e.g., S3, Glue, Redshift, Athena, EMR, Lambda). Experience with Azure or GCP is a plus. Experience building and managing data lakes and data warehouses. Strong understanding of distributed systems and big data processing. More ❯

and PySpark for data processing and automation. Strong command of SQL for data querying, transformation, and performance tuning. Deep experience with cloud platforms , preferably AWS (e.g., S3, Glue, Redshift, Athena, EMR, Lambda). Experience with Azure or GCP is a plus. Experience building and managing data lakes and data warehouses. Strong understanding of distributed systems and big data processing. More ❯

data sets. Collaborate with data scientists to deploy machine learning models. Contribute to strategy, planning, and continuous improvement. Required Experience: Hands-on experience with AWS data tools: Glue, PySpark, Athena, Iceberg, Lake Formation. Strong Python and SQL skills for data processing and analysis. Deep understanding of data governance, quality, and security. Knowledge of market data and its business applications. More ❯

data sets. Collaborate with data scientists to deploy machine learning models. Contribute to strategy, planning, and continuous improvement. Required Experience: Hands-on experience with AWS data tools: Glue, PySpark, Athena, Iceberg, Lake Formation. Strong Python and SQL skills for data processing and analysis. Deep understanding of data governance, quality, and security. Knowledge of market data and its business applications. More ❯

development workflows. Good written and verbal communication; able to contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to .NET More ❯

development workflows. Good written and verbal communication; able to contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to .NET More ❯

development workflows. Good written and verbal communication; able to contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to .NET More ❯

development workflows. Good written and verbal communication; able to contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to .NET More ❯