1 to 25 of 51 Amazon Redshift Jobs in the City of London

Skillset Delivery experience Building solutions in snowflake Insurance experience - advantageous but not necessary MUST HAVE SNOWFLAKE, AWS, SNOWPRO CORE Key Responsibilities: Lead the design and implementation of Snowflake [and Redshift] based data warehousing solutions within an AWS environment Mentoring of team members through code reviews and pair programming Build and support new AWS native cloud data warehouse solutions Develop … experience as a data engineer with a strong focus on Snowflake and AWS services in large-scale enterprise environments Extensive experience in AWS services, e.g. EC2, S3, RDS, DynamoDB, Redshift, Lambda, API Gateway Strong SQL skills for complex data queries and transformations Python programming for data processing and analysis is a plus Strong acumen for application health through performance More ❯

in a Principal or Lead role. Proven experience designing and delivering enterprise data strategies . Exceptional communication and stakeholder management skills. Expertise in enterprise-grade data warehouses (Snowflake, BigQuery, Redshift). Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of data architecture, dimensional modelling, and More ❯

Business Intelligence Engineer Hybrid – London Up to £450 a day Inside IR35 6 Months Key Skills: Business Intelligence (Data modelling, data warehousing, Dashboarding) SQL & Python AWS (S3, Lambda, Glue, Redshift) The Senior Business Intelligence Engineer occupies a unique role at the intersection of technology, marketing, finance, statistics, data mining, and social science. We provide the key insight into customer … 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 ❯

maintain scalable data solutions that empower analytics, reporting, and self-service across the business. Key Responsibilities Build and maintain robust ELT pipelines and cloud-based data warehouses (e.g., AWS Redshift) Model curated data layers to support analytics and decision-making Develop and manage reusable, high-quality data products Promote self-service with intuitive data models and BI tool integration … Ensure compliance, data governance, and security best practices Essential: 3+ years’ experience in data engineering and warehousing Proficiency with SQL, Python, and AWS tools (Redshift, Glue, S3, Lambda, etc.) Strong grasp of data modeling, governance, and pipeline orchestration Excellent communication and collaboration skills in Agile teams Desirable: Experience with dbt, Airflow, Monte Carlo, and BI tools (Power BI, Tableau More ❯

complex datasets SnowPro core certification. AWS Skillset Delivery experience Building solutions in snowflake Insurance experience – advantageous but not necessary Key Responsibilities: Lead the design and implementation of Snowflake [and Redshift] based data warehousing solutions within an AWS environment Mentoring of team members through code reviews and pair programming Build and support new AWS native cloud data warehouse solutions Develop … experience as a data engineer with a strong focus on Snowflake and AWS services in large-scale enterprise environments Extensive experience in AWS services, e.g. EC2, S3, RDS, DynamoDB, Redshift, Lambda, API Gateway Strong SQL skills for complex data queries and transformations Python programming for data processing and analysis is a plus Strong acumen for application health through performance More ❯

maintain scalable data solutions that empower analytics, reporting, and self-service across the business. Key Responsibilities Build and maintain robust ELT pipelines and cloud-based data warehouses (e.g., AWS Redshift) Model curated data layers to support analytics and decision-making Develop and manage reusable, high-quality data products Promote self-service with intuitive data models and BI tool integration … Ensure compliance, data governance, and security best practices 3+ years’ experience in data engineering and warehousing Proficiency with SQL, Python, and AWS tools (Redshift, Glue, S3, Lambda, etc.) Strong grasp of data modeling, governance, and pipeline orchestration Excellent communication and collaboration skills in Agile teams Experience with dbt, Airflow, Monte Carlo, and BI tools (Power BI, Tableau, QuickSight) Knowledge More ❯

data from diverse sources, including APIs like Facebook, Google Analytics, and payment providers. Develop and optimize data models for batch processing and real-time streaming using tools like AWS Redshift, S3, and Kafka. Lead efforts in acquiring, storing, processing, and provisioning data to meet evolving business requirements. Perform customer behavior analysis, gaming analytics, and create actionable insights to enhance … of experience in data engineering roles, with a proven ability to lead and mentor a team. Expertise in SQL, Python, and R. Strong proficiency in AWS technologies such as Redshift, S3, EC2, and Lambda. Experience with Kafka and real-time data streaming technologies. Advanced skills in building ETL pipelines and integrating data from APIs. Familiarity with data visualization and More ❯

it, and transforming complex datasets AWS Skillset Delivery experience Building solutions in snowflake Insurance experience – advantageous but not necessary Key Responsibilities: Lead the design and implementation of Snowflake [and Redshift] based data warehousing solutions within an AWS environment Mentoring of team members through code reviews and pair programming Build and support new AWS native cloud data warehouse solutions Develop … experience as a data engineer with a strong focus on Snowflake and AWS services in large-scale enterprise environments Extensive experience in AWS services, e.g. EC2, S3, RDS, DynamoDB, Redshift, Lambda, API Gateway Strong SQL skills for complex data queries and transformations Python programming for data processing and analysis is a plus Strong acumen for application health through performance More ❯

GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF etc. Excellent consulting experience and ability to design and build solutions … a similar role. Ability to lead and mentor the architects. Required Skills : Mandatory Skills [at least 2 Hyperscalers]: GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF. Preferred Skills : Designing Databricks based solutions for Azure/AWS, Jenkins, Terraform More ❯

GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF etc. Excellent consulting experience and ability to design and build solutions … experience in a similar role. Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF Desirable Skills: Designing Databricks based solutions for Azure/AWS, Jenkins, Terraform More ❯

data enrichment and correlation across primary, secondary, and tertiary sources. Cloud, Infrastructure, and Platform Engineering: Develop and deploy data workflows on AWS or GCP , using services such as S3, Redshift, Pub/Sub, or BigQuery. Containerize data processing tasks using Docker , orchestrate with Kubernetes , and ensure production-grade deployment. Collaborate with platform teams to ensure scalability, resilience, and observability … of data pipelines. Write and optimize complex SQL queries on relational (Redshift, PostgreSQL) and NoSQL (MongoDB) databases. Work with ELK stack (Elasticsearch, Logstash, Kibana) for search, logging, and real-time analytics. Support Lakehouse architectures and hybrid data storage models for unified access and processing. Data Governance & Stewardship: Implement robust data governance , access control , and stewardship policies aligned with compliance More ❯

a data engineering role, ideally in a cloud-native environment Strong programming skills in SQL and Python for data transformation and workflow automation Experience with AWS data tools (e.g. Redshift, Glue, Lambda, S3 ) and infrastructure tools such as Terraform Understanding of data modelling concepts (e.g. dimensional models, star/snowflake schemas) Knowledge of data quality, access controls , and compliance More ❯

excellence — this could be the one. What you’ll do as a Principal Data Engineer: • Lead the architecture and build of modern data platforms using AWS-native tools (S3, Redshift, Lambda, Glue, DynamoDB, Matillion, etc.). • Drive best practices in CI/CD, Infrastructure-as-Code, and data ops methodologies. • Liaise directly with clients to define requirements, shape technical … production-ready. • Be an advocate of clean code, DevOps, and hands-on engineering leadership. Skills you’ll bring as a Principal Data Engineer: • Extensive experience with AWS data services (Redshift, Glue, S3, etc.). • Hands-on with ETL/ELT using Matillion or similar tools. • Strong Python and SQL skills, with a good understanding of data formats • Demonstrated experience More ❯

GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF etc. Excellent consulting experience and ability to design and build solutions … experience in a similar role. Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF Desirable Skills Designing Databricks based solutions for Azure/AWS, Jenkins, Terraform More ❯

GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF etc. Excellent consulting experience and ability to design and build solutions … experience in a similar role. Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF Desirable Skills Designing Databricks based solutions for Azure/AWS, Jenkins, Terraform More ❯

Core Analytics Tooling teams to enhance upstream data sources and develop data processes to enable more scalable and accurate reporting. Basic qualifications Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL etc. Experience with data visualization using Tableau, Quicksight, or similar tools Experience with data modeling, warehousing and building ETL pipelines Experience in Statistical Analysis packages such as … experience (Python) to process data for modeling Experience with SQL Experience in the data/BI space Preferred qualifications Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets If you are interested please apply or send your CV to More ❯

AWS expertise and a consulting mindset as an experienced Principal Data Engineer. Key Responsibilities • Lead and deliver enterprise-grade data engineering solutions using core AWS services (S3, Glue, Lambda, Redshift, Matillion, etc.). • Define architecture, mentor large technical teams, and engage directly with senior client stakeholders. • Own technical responses for RFI/RFP processes, partnering with senior leadership and … engagements. • Strong stakeholder engagement at CxO or Director level. • Deep experience in cloud data lake architectures, ETL/ELT patterns, and metadata/data quality management. • Expertise in Matillion, Redshift, Glue, Lambda, DynamoDB, and data pipeline automation. • Familiarity with data visualisation platforms such as Quicksight, Tableau, or Looker. • Knowledge of CI/CD processes and infrastructure-as-code. • Eligible More ❯

dbt) Track record turning research code into production services (CI/CD, containers etc) Strong SQL and data-management skills; experience querying large analytical databases (Snowflake highly desirable, but Redshift/BigQuery/ClickHouse etc. also welcome). PREFERRED QUALIFICATIONS: Meteorological understanding/experience with weather modelling Prior knowledge or experience in the power markets or energy sector. Experience More ❯

ies (e. g ., Hadoop, Spark, Kafka). Proficiency in cloud platforms such as AWS, Azure, or Goo g le Cloud and cloud-based data services (e.g ., AWS Redshift, Azure Synapse Analytics, Goog le Bi g Query). Experience with DataOps practices and tools, includin g CI/CD for data pipelines. Excellent leadership, communication, and interpersonal skills More ❯

data modeling techniques (conceptual, logical, physical). • Proficiency in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra). • In-depth knowledge of data warehousing concepts and tools (e.g., Redshift, Snowflake, Google BigQuery). • Experience with big data platforms (e.g., Hadoop, Spark, Kafka). • Familiarity with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud). • Expertise More ❯

It suits someone who thrives in greenfield environments, enjoys client engagement, and values clean, scalable, well-documented engineering. Key Responsibilities: Design and build robust data pipelines using AWS (S3, Redshift, Glue, Lambda, Step Functions, DynamoDB). Deliver ETL/ELT solutions with Matillion and related tooling. Work closely with client teams to define requirements and hand over production-ready … solutions. Own infrastructure and deployment via CI/CD and IaC best practices. Contribute to technical strategy and mentor junior engineers. Requirements: Strong hands-on AWS experience – S3, Redshift, Glue essential. Proven experience building ETL/ELT pipelines in cloud environments. Proficient in working with structured/unstructured data (JSON, XML, CSV, Parquet). Skilled in working with relational More ❯

GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF etc. Excellent consulting experience and ability to design and build solutions … experience in a similar role. Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF Designing Databricks based solutions for Azure/AWS, Jenkins, Terraform, StackDriver or More ❯

have requirements: Driven self-starter mentality, with the ability to work independently Python SQL experience building and maintaining ETL/data pipelines expertise in data warehousing - any of BigQuery, Redshift, Snowflake or Databricks is fine experience working with cloud infrastructures - AWS and/or GCP being most advantageous 👍 Bonus points for experience with: Airflow RudderStack, Expo and/or More ❯

and manage DBT models for data transformation and modeling in a modern data stack. Proficiency in SQL , Python , and PySpark . Experience with AWS services such as S3, Athena, Redshift, Lambda, and CloudWatch. Familiarity with data warehousing concepts and modern data stack architectures. Experience with CI/CD pipelines and version control (e.g., Git). Collaborate with data analysts More ❯

thrives in greenfield project environments, and enjoys working both independently and collaboratively. Key Responsibilities as a Principal Data Engineer Propose and implement data solutions using AWS services including S3, Redshift, Lambda, Step Functions, DynamoDB, AWS Glue, and Matillion . Work directly with clients to define requirements, refine solutions, and ensure successful handover to internal teams. Design and implement ETL … to a collaborative, knowledge-sharing team culture. Required Qualifications & Skills Strong experience in ETL processes and cloud data warehouse patterns . Hands-on expertise with AWS services (S3, Glue, Redshift). Proficiency with Matillion for data transformation. Experience working with various relational databases . Familiarity with data visualization tools such as QuickSight, Tableau, Looker, or QlikSense . Ability to More ❯