1 to 25 of 166 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 ❯

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 ❯

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 ❯

environments. Relevant Skills: Essential Skills: Proficiency in Python or Scala for data processing Strong SQL skills for querying and managing relational databases Experience with AWS services including S3, Glue, Redshift, Lambda, and Athena Knowledge of ETL processes and data pipeline development Understanding of data modelling and data warehousing concepts Familiarity with version control systems, particularly Git Desirable Skills: Experience More ❯

environments. Relevant Skills: Essential Skills: Proficiency in Python or Scala for data processing Strong SQL skills for querying and managing relational databases Experience with AWS services including S3, Glue, Redshift, Lambda, and Athena Knowledge of ETL processes and data pipeline development Understanding of data modelling and data warehousing concepts Familiarity with version control systems, particularly Git Desirable Skills: Experience 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

Engineering with strong Python and SQL skills. Background in building and maintaining ETL/ELT pipelines in a cloud environment (AWS or Azure). Knowledge of data warehousing (e.g., Redshift, Postgres) and tools like DBT . Familiarity with CI/CD , data modelling, and Agile practices. Comfortable collaborating with Data Scientists and translating business needs into technical solutions. Experience More ❯

cloud technologies for ETL pipeline, data warehouse and data lake design/building and data movement. AWS data and analytics services (or open-source equivalent) such as EMR, Glue, RedShift, Kinesis, Lambda, DynamoDB. What you can expect Work to agile best practices and cross-functionally with multiple teams and stakeholders. You’ll be using your technical skills to problem More ❯

cloud technologies for ETL pipeline, data warehouse and data lake design/building and data movement. AWS data and analytics services (or open-source equivalent) such as EMR, Glue, RedShift, Kinesis, Lambda, DynamoDB. What you can expect Work to agile best practices and cross-functionally with multiple teams and stakeholders. You’ll be using your technical skills to problem More ❯

cloud technologies for ETL pipeline, data warehouse and data lake design/building and data movement. AWS data and analytics services (or open-source equivalent) such as EMR, Glue, RedShift, Kinesis, Lambda, DynamoDB. What you can expect Work to agile best practices and cross-functionally with multiple teams and stakeholders. You’ll be using your technical skills to problem More ❯

Familiarity with ETL tools and big data platforms. Knowledge of data modelling, replication, and query optimization. Experience with SQL and NoSQL databases. Exposure to data warehousing tools (e.g., Snowflake, Redshift, BigQuery). Data Platform Management Experience in hybrid environments (cloud/on-prem). Skilled in integrating diverse data sources. Understanding of secure data transfer and disaster recovery planning. More ❯

Governance, Security & Compliance - aligned to Data best practices. Liaison with IT Business Systems & Business Teams & Third Parties. Drive Continuous Improvement. Technical Skills Required: Azure Data Factory. AWS Data Services (Redshift, S3, Lambda) - Desirable. SSRS - hands-on experience. ETL - Design, Data Quality Frameworks & Pipeline Management. SQL - Star Schema - Data Modelling. Data Warehouse Design, Development & Testing. Data Warehousing Methodologies. User Support More ❯

Key Skills & Experience: Proven experience as a Senior Data Engineer in a large-scale or complex environment. Strong hands-on expertise with AWS data services (e.g., S3, Glue, Lambda, Redshift, Athena, EMR). Experience building data lakes and modern data platforms from the ground up. Proficiency with Python, SQL, and orchestration tools such as Airflow or dbt. Strong understanding More ❯

years of experience in data engineering or analytics, including designing and delivering enterprise grade data solutions Strong hands-on experience with Snowflake (or comparable cloud data warehouses like BigQuery, RedShift, Synapse) including data modelling, performance tuning and cost management Familiarity with SQL best practices, ELT patterns, and modern data transformation frameworks such as dbt Competence in at least one More ❯

years of experience in data engineering or analytics, including designing and delivering enterprise grade data solutions Strong hands-on experience with Snowflake (or comparable cloud data warehouses like BigQuery, RedShift, Synapse) including data modelling, performance tuning and cost management Familiarity with SQL best practices, ELT patterns, and modern data transformation frameworks such as dbt Competence in at least one More ❯

years of experience in data engineering or analytics, including designing and delivering enterprise grade data solutions Strong hands-on experience with Snowflake (or comparable cloud data warehouses like BigQuery, RedShift, Synapse) including data modelling, performance tuning and cost management Familiarity with SQL best practices, ELT patterns, and modern data transformation frameworks such as dbt Competence in at least one More ❯

years of experience in data engineering or analytics, including designing and delivering enterprise grade data solutions Strong hands-on experience with Snowflake (or comparable cloud data warehouses like BigQuery, RedShift, Synapse) including data modelling, performance tuning and cost management Familiarity with SQL best practices, ELT patterns, and modern data transformation frameworks such as dbt Competence in at least one More ❯