8 of 8 Contract Amazon Redshift Jobs in the UK excluding London

and big data platforms. • Knowledge of data modeling, replication, and query optimization. • Hands-on experience with SQL and NoSQL databases is desirable. • Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) would be beneficial. Data Platform Management: • Comfortable operating in hybrid environments (cloud and on-prem). • Experience integrating diverse data sources and systems. • Understanding of secure data transfer More ❯

and big data platforms. • Knowledge of data modeling, replication, and query optimization. • Hands-on experience with SQL and NoSQL databases is desirable. • Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) would be beneficial. Data Platform Management: • Comfortable operating in hybrid environments (cloud and on-prem). • Experience integrating diverse data sources and systems. • Understanding of secure data transfer More ❯

Proven experience as a Data Architect or Lead Data Engineer in AWS environments* Deep understanding of cloud-native data services: S3, Redshift, Glue, Athena, EMR, Kinesis, Lambda* Strong hands-on expertise in data modelling, distributed systems, and pipeline orchestration (Airflow, Step Functions)* Background in energy, trading, or financial markets is a strong plus* Excellent knowledge of Python, SQL, and More ❯

consistency across various data sources. Document test results and provide detailed reports on data quality findings. Required Skills and Experience: Proven experience with AWS services such as EMR, Lambda, Redshift, Firehose, S3, Iceberg, Athena, and DynamoDB. Strong understanding of data ingestion, parsing, aggregation, and schema validation processes. Proficiency in SQL for data querying and validation. Experience with Python for More ❯

on data architecture Strong proficiency in Python and SQL, with the ability to manipulate and analyse large datasets Hands-on experience with Kafka for stream processing and AWS (particularly Redshift and S3) Skilled in implementing testing and validation strategies to ensure data quality Familiar with version control systems such as Git and working in Agile, collaborative environments Self-driven More ❯

FlowFiles,Processors,ControllerServices, Schedulers,WebUI. Experiencedesigningandoptimizingdataflowsforbatch,real-timestreaming,and event-drivenarchitectures. Abilitytoidentifyandresolveflowissues,optimizeperformance,andimplementerror handlingstrategies. OptionalscriptingskillsforcreatingcustomNiFiprocessors. Programming&DataTechnologies: ProficiencyinJavaandSQL. ExperiencewithC#andScalaisaplus. ExperiencewithETLtoolsandbigdataplatforms. Knowledgeofdatamodeling,replication,andqueryoptimization. Hands-onexperiencewithSQLandNoSQLdatabasesisdesirable. Familiaritywithdatawarehousingsolutions(e.g.,Snowflake,Redshift,BigQuery)would bebeneficial. DataPlatformManagement: Comfortableoperatinginhybridenvironments(cloudandon-prem). Experienceintegratingdiversedatasourcesandsystems. Understandingofsecuredatatransferprotocolsanddisasterrecoveryplanning. CI/CD&DevOpsPractices: ExperienceworkingwithCI/CDpipelinestoautomatedeploymentofNiFiflowsanddata infrastructurecomponents. FamiliaritywithtoolssuchasGit,Jenkins,AzureDevOps,orsimilar. WaysofWorking: ComfortableworkinginAgile/Scrumenvironments,participatinginsprintplanning, stand-ups 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 ❯

to London. This role is ideal for someone with strong experience in data migration, ETL (both batch and real-time), and data warehouse development. What you'll need: DataStage Redshift QuickSight S3 Java SQL Relational databases GitHub/lab experience Experience with DevSecOps and building scalable data platforms Nice to have: Data quality expertise XML knowledge AWS Data Speciality More ❯