8 of 8 Remote Amazon Redshift Jobs in the North of England

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 ❯

Programming experience in Python Skills and experience we’d love you to have... Understanding of cloud computing security concepts Experience in relational cloud based database technologies like Snowflake, BigQuery, Redshift Experience in open source technologies like Spark, Kafka, Beam Good understanding of Cloud providers – AWS, Microsoft Azure, Google Cloud Familiarity with DBT, Delta Lake, Databricks Experience working in an More ❯

Programming experience in Python Skills and experience we’d love you to have... Understanding of cloud computing security concepts Experience in relational cloud based database technologies like Snowflake, BigQuery, Redshift Experience in open source technologies like Spark, Kafka, Beam Good understanding of Cloud providers – AWS, Microsoft Azure, Google Cloud Familiarity with DBT, Delta Lake, Databricks Experience working in an More ❯

pipeline architecture What we're looking for: Proven experience in data engineering at a senior level Strong hands-on knowledge of Databricks Experience with AWS cloud platforms inlcuding S3, Redshift, Glue or Lambda Expertise in data warehousing and ETL processes Ability to work both independently and as part of a collaborative team Why join us? £60,000 salary Flexible 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 ❯

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 ❯

or consumer finance (pricing, underwriting, collections KPIs). Knowledge of marketing analytics (attribution basics, cohort/LTV, churn/retention). Exposure to cloud warehouses (Snowflake/BigQuery/Redshift) and dbt. Comfort working with messy partner data; building validation and reconciliation checks. Basic understanding of experimentation platforms and uplift modelling. Interview Process 1st Stage: Intro with Manager (CV 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 ❯