1 to 25 of 198 Amazon Redshift Jobs

Java Developer – Financial Technology – London/Hybrid (INSIDE IR35) (Key skills: Java, Spring Boot, Kubernetes, AWS EKS, Amazon Redshift, PostgreSQL, RESTful APIs, CI/CD, Microservices, iOS/Android Native, Agile, Financial Services) Are you a highly skilled Java Developer with a passion for building scalable, high-performance financial systems? Do you enjoy working with cutting-edge technologies … integrated with modern mobile and analytics platforms. As part of a collaborative, Agile development team, you will be responsible for building robust microservices, managing data pipelines across PostgreSQL and Amazon Redshift , and delivering performant, secure RESTful APIs used across web and mobile platforms. You’ll work closely with iOS and Android engineers to ensure seamless end-to-end More ❯

Java Developer – Financial Technology – London/Hybrid (INSIDE IR35) (Key skills: Java, Spring Boot, Kubernetes, AWS EKS, Amazon Redshift, PostgreSQL, RESTful APIs, CI/CD, Microservices, iOS/Android Native, Agile, Financial Services) Are you a highly skilled Java Developer with a passion for building scalable, high-performance financial systems? Do you enjoy working with cutting-edge technologies … integrated with modern mobile and analytics platforms. As part of a collaborative, Agile development team, you will be responsible for building robust microservices, managing data pipelines across PostgreSQL and Amazon Redshift , and delivering performant, secure RESTful APIs used across web and mobile platforms. You’ll work closely with iOS and Android engineers to ensure seamless end-to-end More ❯

Java Developer - Financial Technology - London/Hybrid (INSIDE IR35) (Key skills: Java, Spring Boot, Kubernetes, AWS EKS, Amazon Redshift, PostgreSQL, RESTful APIs, CI/CD, Microservices, iOS/Android Native, Agile, Financial Services) Are you a highly skilled Java Developer with a passion for building scalable, high-performance financial systems? Do you enjoy working with cutting-edge technologies … integrated with modern mobile and analytics platforms. As part of a collaborative, Agile development team, you will be responsible for building robust microservices, managing data pipelines across PostgreSQL and Amazon Redshift , and delivering performant, secure RESTful APIs used across web and mobile platforms. You'll work closely with iOS and Android engineers to ensure seamless end-to-end More ❯

Core Azure SQL and MSSQL server Deep understanding of Azure-native services for data engineering. Experience with Azure Key Vault, Azure Monitor, and RBAC. AWS: Experience with S3, Glue, Redshift, and Lambda. Familiarity with IAM, CloudWatch, and Athena. Experience with BigQuery, Cloud Storage, and Dataflow. Familiarity with Cloud Functions, IAM, and Vertex AI (optional). Experience in one or More ❯

engineering role and graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field ● Proficiency in writing SQL queries and knowledge of cloud-based databases like Snowflake, Redshift, BigQuery or other big data solutions ● Experience in data modelling and tools such as dbt, ETL processes, and data warehousing ● Experience with at least one of the programming languages More ❯

experience across data engineering, cloud computing, or data warehousing Minimum 2 years in hands-on development capacity Expertise in one or more modern cloud data platforms: Snowflake, Databricks, AWS Redshift, Microsoft Fabric, or similar Understanding of data modelling principles, dimensional modelling, and database design Proficiency in SQL and query optimization Comprehensive knowledge of ETL/ELT processes and data More ❯

experience across data engineering, cloud computing, or data warehousing Minimum 2 years in hands-on development capacity Expertise in one or more modern cloud data platforms: Snowflake, Databricks, AWS Redshift, Microsoft Fabric, or similar Understanding of data modelling principles, dimensional modelling, and database design Proficiency in SQL and query optimization Comprehensive knowledge of ETL/ELT processes and data More ❯

innovation and technical excellence. Your Profile Essential skills/knowledge/experience: Deep hands-on experience with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks More ❯

innovation and technical excellence. Your Profile Essential skills/knowledge/experience: Deep hands-on experience with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks More ❯

or similar Cloud data ecosystem (AWS) : hands-on experience with core AWS data services. Key services include: S3 for data lake storage AWS Glue for ETL and data cataloging Amazon Redshift or Athena for data warehousing and analytics Lambda for event-driven data processing. ETL/ELT pipeline development : experience in designing, building, and maintaining robust, automated data More ❯

or similar Cloud data ecosystem (AWS) : hands-on experience with core AWS data services. Key services include: S3 for data lake storage AWS Glue for ETL and data cataloging Amazon Redshift or Athena for data warehousing and analytics Lambda for event-driven data processing. ETL/ELT pipeline development : experience in designing, building, and maintaining robust, automated data More ❯

ELT processes, automation Technical Requirements: - Strong proficiency in SQL and Python programming - Extensive experience with data modeling and data warehouse concepts - Advanced knowledge of AWS data services, including: S3, Redshift, AWS Glue, AWS Lambda - Experience with Infrastructure as Code using AWS CDK - Proficiency in ETL/ELT processes and best practices - Experience with data visualization tools (Quicksight) Required Skills More ❯

collaboration across technical and non-technical stakeholders What You’ll Bring Strong hands-on experience with Python for ETL and data engineering Proven expertise in AWS Data Services (Glue, Redshift, S3, Lambda, Databricks) Advanced SQL skills across data modelling, optimisation, and stored procedures Familiarity with MongoDB or other NoSQL databases Understanding of modern data architecture and data governance principles More ❯

or dbt. Strong SQL skills and experience with cloud platforms (Azure preferred). Solid programming background in Python, Scala, or Java. Knowledge of data warehousing solutions (e.g. Snowflake, BigQuery, Redshift). Strong understanding of data governance, security, and compliance (experience within financial services is a plus). Leadership experience, with the ability to mentor, influence, and set technical direction. More ❯

or dbt. Strong SQL skills and experience with cloud platforms (Azure preferred). Solid programming background in Python, Scala, or Java. Knowledge of data warehousing solutions (e.g. Snowflake, BigQuery, Redshift). Strong understanding of data governance, security, and compliance (experience within financial services is a plus). Leadership experience, with the ability to mentor, influence, and set technical direction. More ❯

data engineering experience , including at least 2 years hands-on with modern data platforms. Strong proficiency in SQL , data modelling, and query optimisation. Practical experience with Snowflake, Databricks, AWS Redshift, or Microsoft Fabric . Solid understanding of ETL/ELT pipelines and data warehousing principles . Strong communication and problem-solving skills. Ability to work both independently and collaboratively More ❯

data engineering experience , including at least 2 years hands-on with modern data platforms. Strong proficiency in SQL , data modelling, and query optimisation. Practical experience with Snowflake, Databricks, AWS Redshift, or Microsoft Fabric . Solid understanding of ETL/ELT pipelines and data warehousing principles . Strong communication and problem-solving skills. Ability to work both independently and collaboratively More ❯

to minimise disruption. Collaborate with various teams to align migration processes with organisational goals and regulatory standards. Proficiency in AWS ETL technologies, including Glue, Data Sync, DMS, Step Functions, Redshift, DynamoDB, Athena, Lambda, RDS, EC2 and S3 Datalake, CloudWatch for building and optimizing ETL pipelines and data migration workflows. Working knowledge of Azure data engineering tools, including ADF (Azure More ❯

and big data platforms. Knowledge of data modeling, replication, and query optimization. Hands-on experience with SQL and NoSQL databases is desirable. Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) would be beneficial. Data Platform Management: Comfortable operating in hybrid environments (cloud and on-prem). Experience integrating diverse data sources and systems. Understanding of secure data transfer More ❯

scale that to 500 million events per day. You'll be using Kafka for real-time data streaming and AWS to build, optimise and monitor data warehousing solutions in Amazon RedShift, owning and managing AWS based systems to ensure cost effective, secure and high performance data operations. Location/WFH: You can work from home from anywhere in … data engineering skills and experience, having been through multiple end-to-end data pipeline builds You have a deep knowledge of AWS cloud services including: S3, EC2, Lambda, RDS, RedShift, Glue as well as Kinesis, MongoDB and PostgreSQL You have experience of working in environments with high throughput data (millions of events per hour) You have strong Kafka experience More ❯

AWS (preferred) or Azure , and experience managing data pipelines in the cloud. Strong skills in Python and SQL , with a solid grasp of data warehousing concepts. Experience with DBT , Redshift , or Postgres , and familiarity with BI tools (Power BI preferred). Proven understanding of CI/CD principles , DevOps, and infrastructure automation. Excellent communication skills - able to collaborate across More ❯

persuasively Desirable Skills for the Senior Data Engineer: Experience with event sourcing, dbt, or related data transformation tools Familiarity with PostgreSQL and cloud-native data services (Azure Event Hub, Redshift, Kinesis, S3, Blob Storage, OneLake, or Microsoft Fabric) Understanding of machine learning model enablement and operationalisation within data architectures Experience working within Agile delivery environments If you are an More ❯

Requirements Proven experience as a Data Engineer, with a track record of designing and managing scalable data pipelines and infrastructure in AWS. Strong expertise with AWS services, including Glue, Redshift, Data Catalog, and large-scale data storage solutions such as data lakes. Proficiency in ETL/ELT tools (e.g. Apache Spark, Airflow, dbt). Skilled in data processing languages More ❯

see technical skills), delivering scalable, performant, reliable solutions. Strong data reliability/observability, data governance and information security credentials. What technical skills are required? ETL/ELT & Data Transformation: Amazon Redshift (query tuning, distribution/sort keys, workload management) Data modelling (normalisation, dimensional) dbt (modeling, testing, documentation, deployment) Building scalable ETL/ELT pipelines with Python Workflow Orchestration More ❯

warehousing, data lakes, and ETL processes. Programming: Experience with programming languages like Python, Java, or Scala. Cloud Data Platform: Strong experience with Cloud Data Platform like Databricks (preferred) , Snowflake, Redshift, etc. Databricks Expertise: Deep understanding of Databricks architecture, including clusters, jobs, notebooks, and workspaces. Database Technologies: Knowledge of relational and NoSQL databases. Infrastructure as Code: Experience with tools like More ❯