12 of 12 Amazon Athena Jobs in London

Job ID: Amazon Web Services Australia Pty Ltd Are you a Senior Data Analytics and 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 ❯

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 ❯

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 ❯

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 ❯

Responsibilities Proven experience as a Data Architect or Lead Data Engineer in AWS environments Deep understanding of cloud-native data services: S3, Redshift, Glue, Athena, EMR, Kinesis, Lambda Strong hands-on expertise in data modelling, distributed systems, and pipeline orchestration (Airflow, Step Functions) Background in energy, trading, or financial markets is a strong plus Excellent knowledge of Python, SQL More ❯

Proven experience as a Data Architect or Lead Data Engineer in AWS environments* Deep understanding of cloud-native data services: S3, Redshift, Glue, Athena, EMR, Kinesis, Lambda* Strong hands-on expertise in data modelling, distributed systems, and pipeline orchestration (Airflow, Step Functions)* Background in energy, trading, or financial markets is a strong plus* Excellent knowledge of Python, SQL, and 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 ❯

engage with clients, learn domain knowledge, be proactive and curious in addition to standard tech would be ideal for the role. Tech Stack: AWS - S3 for storage, Lambda functions, Athena (thus strong SQL), Glue, Glue Data Catalog Python Current frontend is Tableau but experience with any of them will be interchangeable DevOps experience a bonus e.g. Terraform, Drone, Kubernetes More ❯

will act as a bridge between business and technical stakeholders, working closely with engineers, architects, and product teams. Key Responsibilities SQL Data Model Analysis – Analyse Oracle SQL and AWS Athena data models; write and run SQL queries to validate structures and business logic. Requirement Review & Refinement – Review, refine, and maintain requirements based on current-state analysis and stakeholder input. … in Jira , and support iterative delivery. Required Skills & Experience 8+ years as a Technical Business Analyst in data platforms or migration projects. Strong SQL proficiency (Oracle SQL and AWS Athena). Hands-on experience with data model analysis, requirement capture, and refinement . Proven track record in cloud migration projects , ideally involving AWS. Familiarity with data warehousing, ETL/ More ❯