26 to 50 of 160 Amazon Redshift Jobs in England

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 ...

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 ...

hands‐on experience in a data engineering role Strong proficiency in SQL and Python Strong experience with AWS (Batch, Lambda, Glue, ECR, RDS, Redshift, S3) Experience in data warehousing, database design (e.g., star schema, snowflake schema), and data modelling. Excellent problem‐solving skills and the ability to work independently ...

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 ...

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 ...

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 ...

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 ...

backlog management tools Power BI, Tableau, Qlik or Looker Matillion, Talend, Pentaho, SSIS Databricks, DBT, Fivetran Snowflake, Microsoft SQL Server, Oracle DB or Redshift Building CI/CD pipelines and IaC Analytical skills including the ability to apply a range of analytics, visualisation and data science techniques Strong understanding ...

Build Tool) or similar data transformation frameworks is essential. Data Warehousing: Experience working with cloud‐based data warehouses such as Snowflake, Google BigQuery, or Amazon Redshift. Data modelling: Solid understanding of data warehousing concepts, ETL/ELT principles, and dimensional modelling techniques. Version Control: Proficiency with Git for collaborative ...

expect candidates to have worked with all of them: Cloud data platforms, warehouses and lakehouses: Databricks, Snowflake, Microsoft Fabric, Azure Synapse, Google BigQuery, Amazon Redshift Data engineering and orchestration: Spark, dbt, Airflow, Azure Data Factory, AWS Glue, Dataflow, Kafka, Flink Governance, catalogue and lineage: Microsoft Purview, Collibra, Informatica … Alation, Atlan, OpenLineage Graph, ontology and semantic technologies: Neo4j, Amazon Neptune, Stardog, GraphDB, RDF, OWL, SPARQL AI/ML data infrastructure: vector databases and search platforms such as Pinecone, Weaviate, Milvus, Azure AI Search, OpenSearch or pgvector; feature stores such as Feast or Tecton; model lifecycle and experiment tracking ...

implementing: Data Lakes Big Data Analytics platforms Cloud-based solutions experience AWS preferred Software Engineering Expertise with: RDBMS Data Warehousing Data Modelling Experience with: Redshift PostgreSQL NoSQL databases DevOps & Infrastructure Proficiency in: DevOps practices CI/CD pipeline management Infrastructure as Code (IaC) Nice-to-Have Hands-on experience ...

designing end-to-end data systems. Technical proficiency: Solid expertise in SQL and Python, experience with cloud data warehouses (e.g., BigQuery, Snowflake, or Redshift), and data transformation tools (such as dbt). Pipeline mastery: Practical experience building and operating batch or streaming pipelines using orchestration tools like Airflow, Prefect ...

designing and implementing data solutions. Proficiency in programming languages such as Python, Java, or Scala. Strong experience with data warehousing technologies (e.g., Snowflake, Redshift) and proficiency in SQL. Experience of working in an event-driven architecture environment and cloud platforms (e.g, AWS, Azure, GCP). Familiarity with data governance ...

Leads) and driving high-level database modernization strategy. Legacy Data Warehouse & Modernization Architecture understanding of legacy EDW systems (any of Teradata, Netezza, Snowflake, Synapse, Redshift, and Exadata) and architectures required to successfully transition workloads to the Databricks Data Intelligence Platform. Mastery of migration migrations scope & progression taking customers from ...

modern data platforms and data architecture Experience designing and explaining Lakehouse and Data Warehouse architectures using technologies such as Databricks, Snowflake, Microsoft Fabric, BigQuery, Redshift, or similar Strong understanding of ETL/ELT, analytics and BI, stream vs batch processing, and Medallion Architecture Familiarity with the Data Science ...

developing enterprise-wide data strategies and transformation roadmaps.Experience supporting organisational transformation and continuous improvement programmes through insight and analytics.Familiarity with Microsoft Fabric, Azure Synapse, Amazon Redshift or Google BigQuery.Experience overseeing the deployment of AI, machine learning or advanced analytics solutions into production environments.Professional qualifications in Project, Programme ...

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 ...

Lead Data Engineering aspects of projects. Qualifications Substantial experience in a full life cycle of date. Including familiarity with data related AWS technologies (e.g. Redshift). Strong programming skills and substantial experience designing and building data pipelines (e.g. Python, SQL, Airflow). Experience in data standardisation and QA techniques. ...

databases, and third-party systems. Data Warehousing Knowledge: You understand modern data warehouse architectures and have experience working with cloud-based solutions such as Amazon Redshift, Snowflake, or BigQuery. Data Quality & Reliability: You have a strong understanding of data quality principles, automated testing, validation, and monitoring, with ...

Agile team. You bring 5+ years in data engineering, strong Oracle 19c+ experience, warehousing concepts, ETL/ELT, and cloud familiarity (AWS Redshift/RDS). Bonus familiarity with dbt and CI/CD will help you improve data quality and performance. #J-18808-Ljbffr ...

Date: ASAP OR 4 weeks. Must-Have Skills: Strong experience building and supporting AWS Data Lakehouse solutions AWS services including S3, Glue, EMR, Athena, Redshift, Lake Formation, EventBridge & Step Functions Advanced Python and SQL skills Strong experience with PySpark and large-scale data processing Hands-on experience with ...

build and manage automated data pipelines. Cloud Data Platforms: Hands-on experience with Snowflake (highly desirable) or similar cloud-based data warehouses (e.g., BigQuery, Redshift). Additional Programming: Knowledge of C# and experience working within a .NET environment. AI Tooling: Experiencing utilising AI-assisted development tools, such as Github ...

strong grasp of software engineering principles applied to data (version control, automated testing, CI/CD).Strong background working with cloud analytics platforms (Redshift, BigQuery, Snowflake), transformation tools (dbt), and modern visualisation software (Omni, Looker, Tableau, Power BI).Experience establishing data governance and data quality standards.Experience driving self-serve ...

Strong expertise designing and implementing cloud-based data architectures, particularly within AWS environments. Deep technical knowledge of AWS services, including EC2, S3, RDS, Lambda, Redshift , and related data services. Proven experience designing secure architectures within sensitive or highly regulated environments. Hands-on experience with Apache Flink and real-time ...