1 to 25 of 44 Amazon Redshift Jobs in London

management of large-scale enterprise data warehouse solutions. Build and maintain data integration and transformation processes using IBM DataStage. Work with AWS technologies including Amazon Redshift, Amazon S3, AWS Glue and Amazon QuickSight. Develop and optimise SQL-based data transformations and work with relational databases. Support … need strong commercial data engineering experience, particularly across enterprise-scale ingestion, transformation, warehousing and database environments. Essential skills and experience IBM DataStage Amazon Redshift Amazon S3 AWS Glue Amazon QuickSight AWS data/cloud environments ETL and data migration Batch and real-time data processing Enterprise ...

from data lakes and lakehouses to real-time streaming pipelines, business intelligence, and advanced analytics leveraging the breadth of AWS's analytics portfolio including Amazon Redshift, Athena, EMR, Glue, Kinesis, QuickSight, and OpenSearch. You'll serve as a trusted technical advisor to enterprise customers navigating complex analytics modernisation … through thought leadership, workshops, and reference architectures. Key job responsibilitiesArchitect analytics solutions — design data lake, lakehouse, warehouse, and streaming architectures using AWS analytics services (Redshift, Athena, EMR, Glue, Kinesis, QuickSight, OpenSearch)Lead analytics modernisation — guide customers migrating from legacy platforms (Teradata, Oracle, Netezza, Hadoop) to cloud-native analytics, including ...

warehouse, data mesh, data fabric).Hands-on experience with one or more cloud data ecosystems: Azure (Data Factory, Synapse, Fabric, ADLS, Databricks)AWS (Glue, Redshift, EMR)GCP (BigQuery, Dataflow)Databricks (Spark/PySpark)Snowflake (SQL, Snowpark, performance tuning)Desirable ExperienceStrong SQL and/or Python capability, and familiarity with ...

Cloud, or Azure) Experience with large-scale distributed data processing and performance tuning Hands-on experience with modern data warehousing/lakehouse technologies (e.g., Redshift, BigQuery, Snowflake; and engines such as Spark, Flink, or Trino; and table formats such as Iceberg, Hudi, or similar) Strong SQL skills and experience ...

Cloud, or Azure) Experience with large-scale distributed data processing and performance tuning Hands-on experience with modern data warehousing/lakehouse technologies (e.g., Redshift, BigQuery, Snowflake; and engines such as Spark, Flink, or Trino; and table formats such as Iceberg, Hudi, or similar) Strong SQL skills and experience ...

Cloud, or Azure) Experience with large-scale distributed data processing and performance tuning Hands-on experience with modern data warehousing/lakehouse technologies (e.g., Redshift, BigQuery, Snowflake and engines such as Spark, Flink, or Trino and table formats such as Iceberg, Hudi, or similar) Strong SQL skills and experience ...

scripting preferred Strong Knowledge of all phases of the system development life cycle Experience with major database and big data platforms (e.g. RDS, Aurora, Redshift, Data bricks, MySQL, Oracle, PostgresSQL, Hadoop, Snowflake, etc.) Understanding and experience with major Data Architecture philosophies (Dimensional, ODS, Data Vault, etc.) Understanding of modern ...

Excellent knowledge of AWS and components such as S3, Kinesis, DMS, SNS, Glue, Athena, RDS Experience with Data Warehouse databases like Snowflake/Redshift/BigQuery Experience with Python/PySpark Experience with implementing Rest APIs. Experience with using and integrating BI tools such as QuickSight, Looker, Power ...

stakeholders Experience supporting machine learning or AI workloads through production-grade data engineering solutions Highly Desirable Strong AWS data platform experience (S3, Glue, EMR, Redshift, Athena, Lambda, Bedrock, SageMaker or equivalent) Experience operationalising machine learning models into production environments Experience with MLOps, model deployment, model monitoring, model lifecycle management ...

scripting preferred Strong Knowledge of all phases of the system development life cycle Experience with major database and big data platforms (e.g. RDS, Aurora, Redshift, Data bricks, MySQL, Oracle, PostgresSQL, Hadoop, Snowflake, etc.) Understanding and experience with major Data Architecture philosophies (Dimensional, ODS, Data Vault, etc.) Understanding of modern ...

dimensional modeling, and ELT/ETL design, with production experience on a modern cloud data warehouse or lakehouse (for example Snowflake, Databricks, BigQuery, Redshift, or Synapse) and a transformation framework such as dbt. Experience applying software engineering practices to analytics work, including Git-based workflows, automated testing ...

GenAI/LLM techniques to data and analytics. Enterprise-level experience with at least one large-scale analytical data warehouse or query engine: StarRocks, Amazon Redshift, Snowflake, Databricks, or Trino. Expertise writing, optimizing, and analyzing SQL.Hands-on experience building and operating distributed data platforms on AWS or GCP.Hands ...

role focused on building scalable, secure and high-performing solutions that support analytics, AI, and enterprise reporting. Key Skills Required AWS (S3, Glue, Redshift, Athena, Kinesis, Lambda) Data Lake & Lakehouse architectures ETL/ELT & data pipelines Python, SQL & PySpark Data modelling (Kimball, Data Vault) Data governance & security Terraform/ ...

bash/linux. Experience developing cloud-native data platforms and solutions on AWS, including working with cloud data warehouse technologies such as Amazon Redshift and applying data modelling best practices. Good understanding of software engineering principles, including object-oriented development, testing practices, version control, code quality management … specialist discipline Familiarity with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and other patterns used to support Generative AI solutions on platforms such as Amazon Bedrock. Experience developing data-based apps in Streamlit/Shiny Skills in 'Big Data' technology tools like Hadoop/Spark Knowledge of Infrastructure ...

Engineer Must have: Experience in building complex data pipelines/ETL/ELT scriptsExtensive experience with SQLExperience with Data Warehouse databases like Snowflake/Redshift/BigQueryExperience with PythonPreferably have some knowledge of AWS and components such as S3, Kinesis, DMS, SNS, Glue, Athena, RDSExperience with implementing Rest APIs. ...

pipelines will be built in PySpark SQL Knowledge of AWS and components such as S3, Glue, Athena, RDS Experience with Data Warehouse databases like Redshift/Snowflake/BigQuery Experience with implementing Rest APIs. Experience with using and integrating BI tools such as Looker, Qlik, Power BI, Tableau Modern ...

designing and maintaining ETL/ELT pipelines Exposure to data warehousing, data lakes and modern data architecture Experience with cloud data platforms (AWS preferred - Redshift, Athena, S3, Glue. Azure accepted) Understanding of workflow orchestration and automation tools Python experience (including PySpark) is beneficial but not essential Exposure ...

Azure AI Foundry, Azure AI Search (vector/RAG), Azure Machine Learning, Azure AI Agent Service, Semantic Kernel, Prompt Flow and Content Safety. AWS: Amazon Bedrock (including Knowledge Bases and Agents), Amazon SageMaker, Amazon Q, Amazon OpenSearch (vector), and Guardrails for Amazon Bedrock. Expertise … based platform (AWS or Azure); AI or machine learning specialism desired. Familiarity with modern data and lakehouse ecosystems (e.g. Microsoft Fabric, Databricks, Snowflake, Synapse, Redshift) as a foundation for grounding AI.Soft SkillsStrong leadership and programme management skills, with the confidence and directive to challenge the status quo and align ...

communication skills. Desirable Skills Experience within Credit Cards or broader consumer lending environments. Knowledge of AWS data services such as S3, Glue, Lambda, Redshift or related technologies. Experience working within regulated financial services environments. Understanding of modern data architecture and cloud data strategy initiatives. Candidate Profile The ideal candidate ...

trace transformations Databricks, including Unity Catalog and medallion (bronze-silver-gold) architecture Azure or AWS data services (e.g. Data Factory, Synapse, S3, Glue, Redshift) Data testing tools such as dbt tests, Great Expectations or Soda YAML-based configuration or structured test frameworks Using AI agents and LLMs ...

fintech, SaaS, or digital platforms Deep proficiency in SQL and hands-on experience with dbt Experience working with modern data warehouses (Snowflake, BigQuery, or Redshift) Familiarity with software engineering principles (Git, CI/CD, testing frameworks) Strong understanding of data visualisation and BI tools Confident communicator able to translate ...

Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and/or implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset....) SDLC and DevOps ...

data integrationSkilled in data manipulation, processing and orchestration frameworksHands-on experience with Data Factory, Databricks, SQL DB, Synapse, Stream Analytics, Glue, Airflow, Kinesis, Redshift, SonarQube and PyTestProficiency with GitHub, GitHub Actions and Azure DevOpsStrong communication and collaboration skills to align technical and business stakeholdersProven ability to lead solution delivery ...

Data Architect or similar data-led engineering role. Strong technical capability across data modelling, integration, governance, and transformation. Experience with AWS (S3, Glue, Redshift, Lambda, Kinesis) and/or Azure (ADF, Synapse, Fabric). Familiarity with modern data platforms (e.g. Databricks, Snowflake, or Lakehouse environments). Ability to operate ...

different platforms, and you’ll be expected to work across them. Any of the major clouds, with native services such as S3, Glue, Redshift and Kinesis on AWS, Data Factory, Synapse and Event Hubs on Azure, or BigQuery, Dataflow and Pub/Sub on GCP Databricks and Snowflake running ...