12 of 12 Amazon Redshift Jobs in the North of England

introduction of streaming and real-time data processing alongside traditional batch systems. Mentoring junior engineers and sharing best practices to strengthen data engineering capability. Tech Stack & Environment AWS ecosystem: Redshift, S3, Glue, Lambda, Step Functions, CloudFormation Core tools: Python, SQL, DBT, Terraform, GitHub, CI/CD Data warehousing: 600TB+ environment with expansion into Databricks BI & analytics: Power BI, Tableau More ❯

engineers and support their growth. Implement best practices for data security and compliance. Collaborate with stakeholders and external partners. Skills & Experience: Strong experience with AWS data technologies (e.g., S3, Redshift, Lambda). Proficient in Python, Apache Spark, and SQL. Experience in data warehouse design and data migration projects. Cloud data platform development and deployment. Expertise across data warehouse and More ❯

/CD pipelines, IaC, monitoring systems to ensure scalable, reliable data workflows. You bring professional experience with the following tools : AWS data tooling such as S3/Glue/Redshift/SageMaker. Familiarity with containerization (e.g., Docker/ec2), Orchestration in enterpirse environment (Airflow), Infrastructure automation (Terraform), CI/CD platform (Github Actions & Admin), Password/Secret management (hashicorp 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 ❯

machine learning, and next-gen data architecture. What You’ll Do Build and deliver robust, scalable data pipelines using Python and SQL. Model and transform data in Databricks, AWS Redshift, and other modern platforms. Integrate new systems into our Group Data Warehouse, enabling faster, smarter insights. Collaborate with stakeholders to understand business needs and deliver data solutions that drive More ❯

consultants. Knowledge and Skills: Knowledge - Broad data management technical knowledge so as to be able to work across full data cycle. - Proven Experience working with AWS data technologies (S3, Redshift, Glue, Lambda, Lake formation, Cloud Formation), GitHub, CI/CD - Coding experience in Apache Spark, Iceberg or Python (Pandas) - Experience in change and release management. - Experience in Database Warehouse … procedures. Technical Essentials: - Expertise across data warehouse and ETL/ELT development in AWS preferred with experience in the following: - Strong experience in some of the AWS services like Redshift, Lambda,S3,Step Functions, Batch, Cloud formation, Lake Formation, Code Build, CI/CD, GitHub, IAM, SQS, SNS, Aurora DB - Good experience with DBT, Apache Iceberg, Docker, Microsoft BI More ❯

Hands-on with Docker and Kubernetes for containerization and orchestration. Strong experience with REST APIs, FastAPI/Flask, and backend microservices . Solid database skills ( PostgreSQL, MySQL, DynamoDB, MongoDB, Redshift, Snowflake ). Excellent knowledge of CI/CD pipelines and DevOps practices. Experience with Agile/Scrum delivery models . Strong communication and ability to mentor junior developers More ❯

data manipulation techniques. Excellent analytical, problem-solving, and critical thinking skills. Proven ability to communicate technical findings to non-technical stakeholders. Preferred: Experience with cloud data platforms (e.g., AWS Redshift, Google BigQuery, Snowflake). Familiarity with A/B testing, forecasting, and predictive modelling techniques. Experience in eCommerce as well as Finance and Healthcare industries. This fantastic new role More ❯

Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift for efficient loading strategies and write ETL pipelines that handle large volumes of data efficiently, with low latency. Location/WFH: You'll join a small but growing team More ❯

to reduce time-to-production for experiments and prototypes. Design and optimize data wrangling and transformation workflows using Python. Leverage AWS cloud services (EC2, S3, Lambda, SageMaker, RDS, DynamoDB, Redshift, etc.) to build robust, scalable, and cost-effective solutions. Apply AIOps practices to enhance monitoring, automation, and resilience of ML systems. Implement best practices in data engineering, version control … background in data structures, algorithms, and software engineering principles. Advanced proficiency in Python for data wrangling, pipeline automation, and ML workflows. Expertise in AWS services, including databases (RDS, DynamoDB, Redshift) and machine learning/AI (SageMaker, AI/ML frameworks). Hands-on experience with ML pipeline orchestration, CI/CD, and deployment automation. Deep understanding of ML Ops More ❯

scientists, and engineers to unlock automation, enable BI, and increase advanced analytics. What You'll Be Doing: Designing and building robust data pipelines using AWS Glue, Lambda, S3, and Redshift Leading the migration of legacy systems to a modern AWS architecture Ensuring data quality, integrity, and performance across platforms Developing scalable lakehouse and warehouse solutions Operationalizing machine learning models … Mentoring junior engineers and sharing best practices Staying ahead of the curve with emerging data technologies What You'll Bring: Solid hands-on experience with AWS (Glue, Lambda, S3, Redshift, EMR) Strong Python, SQL, and PySpark skills Deep understanding of data warehousing and lakehouse concepts Problem-solving mindset with a focus on performance and scalability Excellent communication skills across More ❯

data platforms. The role focuses on AWS data services, IaC, CI/CD, and orchestration, supporting secure and scalable data operations. Responsibilities: Build and maintain AWS data services (S3, Redshift, Athena, Glue, Batch, Lambda, OpenSearch). Deliver Infrastructure as Code with Terraform. Manage workflows using Airflow and CI/CD pipelines (GitLab/GitHub). Monitor and secure data … infrastructure, access, and usage. Support data engineering environments with recovery, optimisation, and automation. Troubleshoot issues and contribute to process/documentation improvements. Experience: Essential: Strong AWS services experience (S3, Redshift, Athena, Glue, Batch, Lambda, Step Functions, SQS, EMR). Terraform (IaC), Airflow (orchestration), CI/CD (YAML, GitLab/GitHub). Python, SQL, Bash. AWS security/IAM, VPC More ❯