15 of 15 Remote Amazon Redshift Jobs in London

strategic business decisions. Responsibilities for the AWS Data Engineer: Design, build and maintain scalable data pipelines and architectures within the AWS ecosystem Leverage services such as AWS Glue, Lambda, Redshift, EMR and S3 to support data ingestion, transformation and storage Work closely with data analysts, architects and business stakeholders to translate requirements into robust technical solutions Implement and optimise More ❯

based architecture. You will need to have skills and experience in the following: Cloud Data Architecture: Strong knowledge of modern, cloud-based data architecture and tooling (e.g., S3, Glue, Redshift, Athena, Lake Formation, Iceberg/Delta). AWS Platform Build: Demonstrable experience designing and building modern data platforms in AWS. ETL/Orchestration Expertise: Expertise in ETL/ELT More ❯

based architecture. You will need to have skills and experience in the following: Cloud Data Architecture: Strong knowledge of modern, cloud-based data architecture and tooling (e.g., S3, Glue, Redshift, Athena, Lake Formation, Iceberg/Delta). AWS Platform Build: Demonstrable experience designing and building modern data platforms in AWS. ETL/Orchestration Expertise: Expertise in ETL/ELT 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 ❯

SC cleared, or eligible to obtain SC-level security clearance Job description We are looking for a developer with expertise in Python, AWS Glue, step function, EMR cluster and redshift, to join our AWS Development Team. You will be serving as the functional and domain expert in the project team to ensure client expectations are met. The role involves More ❯

what to do, run some whiteboard design sessions (realising you've used a permanent marker, you quickly leave the room) Qualifications Data Warehousing, Data Modelling, Database Design, ETL AWS Redshift, AWS Glue, S3, SQL Server, Power BI Cloud/DevOps AWS, Docker, Terraform Bitbucket, Bamboo, CI/CD deploy pipeline Agile, pair programming, code reviews Additional Information Were a More ❯

and eventual consistency systems using Kafka, .Net, Java, REST APIs, AWS, Terraform and DevOps Nice to have:experience in data pipping and modelling using SQL, DBT, ETL, Data Warehousing, Redshift and Python, and ecommerce and mobile applications background Additional Information Were a community here that cares as much about your life outside work as how you feel when youre More ❯

Collaborative, curious, and happy to work in a self-organising, fast-paced environment. Nice-to-Have Skills: Experience with GCP/BigQuery or other cloud data warehouses (e.g., Snowflake, Redshift). Familiarity with data orchestration tools (e.g., Airflow). Experience with data visualisation platforms (such as Preset.io/Apache Superset or other). Exposure to CI/CD pipelines More ❯

Collaborative, curious, and happy to work in a self-organising, fast-paced environment. Nice-to-Have Skills: ·Experience with GCP/BigQuery or other cloud data warehouses (e.g., Snowflake, Redshift). ·Familiarity with data orchestration tools (e.g., Airflow). ·Experience with data visualisation platforms (such as Preset.io/Apache Superset or other). ·Exposure to CI/CD pipelines More ❯

experience (AWS or GCP) with services for compute, data, and AI/ML. Proven skills in data engineering (ETL pipelines, APIs, SQL/NoSQL, data warehouses like BigQuery/Redshift). Experience with AI agents, LLMs and orchestration frameworks (LangChain, AutoGen, LlamaIndex, etc.). Demonstrated ability to ship production-ready internal tools or SaaS integrations. Strong problem-solver who More ❯

in commercial analytics, ideally with marketing or customer analytics exposure. Strong SQL skills with experience in dbt or similar modelling frameworks. Experience with modern cloud data warehouses (BigQuery, Snowflake, Redshift, etc.). Skilled in dashboarding tools (Looker, Power BI, etc.). Comfortable working with Marketing/User Acquisition teams. Understanding of advertising platform constraints (Meta, Google, mobile tracking). More ❯

Key Requirements About You Proficient in SQL, with experience querying and transforming large datasets across marketing, sales, and customer data sources. Comfortable working with modern data stacks, ideally including Redshift, BigQuery, Matillion, Metabase, and Retool. Strong grasp of performance marketing metrics such as ROAS, CAC, CTR, CPM, and attribution models. Experienced in building dashboards and visualisations that enable data More ❯

IQ, Adobe Analytics, GTM and Adobe Dynamic Tag Manager) changes. Integrate data sources via web and REST APIs. Data pipping and modelling using SQL, DBT, Airflow, ETL, Data Warehousing, Redshift and Python. Transfer knowledge of the business processes and requirements to the development teams. Collaborate with Product, Marketing and Development teams to collect business requirements and translate them into More ❯

features and ensuring high-fidelity cloud platform emulation to help developers test locally with speed and confidence. Requirements What you will be working on/responsible for Ensure Snowflake, Redshift, Athena, Glue, and future emulators are kept up to date with the latest syntax, behaviors, and APIs. Identify and resolve bugs, edge cases, and inconsistencies across emulated services. Maintain … warehouses, including SQL engines, query planning, storage layers, indexing, and SQL parsing/ASTs, with experience developing database features. Hands-on experience with cloud data platforms such as Snowflake, Redshift, Athena, or BigQuery, including optimization techniques and custom parsers/transpilers. Practical knowledge of distributed and analytical engines (e.g., Apache Spark, Trino, PostgreSQL, DuckDB) with skills in query engines More ❯

integrity, scalability, and cost efficiency Managing complex data workflows and ML pipelines Ensuring model quality and performance Partnering cross-functionally across engineering, science, and product Tech Stack: Spark, Cassandra, Redshift AI/ML Use Cases: Predictive click models, data quality optimization, GenAI search applications What You'll Bring 5-10 years' experience overall, with 3+ years in data engineering More ❯