7 of 7 Permanent Amazon Redshift Jobs in Leeds

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 ❯

development projects, data modelling, and cloud data platform deployments. Mentor data engineers and contribute to best practices across the team. Key skills: Strong experience with AWS data services (S3, Redshift, Glue, Lambda, Lake Formation, CloudFormation). Proficiency in SQL, Python (Pandas), Spark or Iceberg. Experience with data warehouse design, ETL/ELT, and CI/CD pipelines (GitHub, CodeBuild 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 ❯

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 ❯

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 ❯