significant exposure to large-scale data architectures and cloud-based solutions. Has following technical skills: o Expert-level proficiency in SQL (e.g., MySQL, PostgreSQL, Redshift) and NoSQL databases (e.g., MongoDB, Cassandra). o Proficiency in one or more programming languages (e.g., Python, Scala, Java) for data integration, automation, and More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
Exeter, England, United Kingdom Hybrid / WFH Options
jobs24.co.uk
in the cloud (AWS, Azure, GCP), while also gaining opportunities to learn about and use data services such as Databricks, Data Factory, Synapse, Kafka, Redshift, Glue, Athena, BigQuery, S3, Cloud Data Fusion etc. Responsibilities You're an engineer at heart and enjoy the challenge of building reliable, efficient data More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
Manchester, England, United Kingdom Hybrid / WFH Options
Smart DCC
and Systems Manager. Serverless platforms such as Lambda, SQS, Fargate, and API Gateway. RDS experience and exposure to DataLake/LakeHouse platforms such as RedShift, Glue, and Athena and IAM roles and policies. Deep experience and strong skills with Terraform and Git. Experience troubleshooting server and software configuration issues More ❯
professional with a proven ability to lead and inspire teams. You bring deep technical skills in Python, SQL, and AWS services such as EC2, Redshift, Lambda and Kinesis, alongside strong stakeholder management and commercial awareness. You’ll also bring: Proven experience designing and implementing data pipelines, ETL processes, and More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
services. Proficiency in one or more programming languages including Java, Python, Scala or Golang. Experience with columnar, analytical cloud data warehouses (e.g., BigQuery, Snowflake, Redshift) and data processing frameworks like Apache Spark is essential. Experience with cloud platforms like AWS, Azure, or Google Cloud. Strong proficiency in designing, developing More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
how these can be practically applied. Experience with Python or other scripting languages Good working knowledge of the AWS data management stack (RDS, S3, Redshift, Athena, Glue, QuickSight) or Google data management stack (Cloud Storage, Airflow, Big Query, DataPlex, Looker) About Our Process We can be flexible with the More ❯
platforms and cloud data solutions . Hands-on experience designing data solutions on Azure (e.g., Azure Data Lake, Synapse, Data Factory) and AWS (e.g., Redshift, Glue, S3, Lambda) . Strong background in data architecture , including data modeling, warehousing, real-time and batch processing, and big data frameworks. Proficiency with More ❯
ease of downstream integration and rapid onboarding of new events or features. Data Egestion: Develop and manage data pipelines for exporting curated datasets from Redshift to platforms like Salesforce and Gainsight using reverse ETL tools (e.g., Hightouch). Data Ingestion: Own end-to-end responsibility for ingesting key productivity More ❯
