5 of 5 Apache Spark Jobs in the Thames Valley

transformation. Proficiency in Python and PySpark for advanced data engineering, machine learning, and large-scale distributed processing within Databricks. Hands-on experience with Spark optimizations (Adaptive Query Execution, caching, partitioning, broadcast joins) to deliver performant solutions for big data workloads. Advanced knowledge of BI and visualization tools such ...

ServiceNow Automation, Automation Anywhere, Camunda, or similar). Proven experience in AI/ML, data modeling, data lakes, event streaming, and analytics (e.g., Kafka, Spark, Python ML stack). Deep exposure to telecom protocols and domains Experience with cloud-native architectures (Azure/AWS/GCP), containerization, and DevSecOps ...

architectures using Delta Lake principles Ingest, transform, and curate data from multiple sources (APIs, databases, files, streaming) Develop scalable data transformations using PySpark and Spark SQL Implement data models optimized for analytics and reporting (e.g. star schemas) Monitor, troubleshoot, and optimize performance and cost of data workloads Apply data … version control (Git) and collaborative development workflows Nice to Have Experience with Power BI and semantic models Exposure to streaming technologies (Kafka, Event Hubs, Spark Structured Streaming) Infrastructure-as-code experience (Bicep, Terraform) CI/CD tooling (Azure DevOps, GitHub Actions) Familiarity with data governance and cataloging tools Experience ...

Azure based Production Data & Analytics ETL/integration solutions (Fabric, Databricks, Synapse, Data Factory, Function Apps, Power BI etc) against SLAs Python, PySpark, Scala, Spark SQL Ability to identify and investigate complex problems and implement resolutions Direct contact with customers/end-users on the phone and by email ...

team engineering organisations Strong background in distributed systems, large-scale data pipelines and ML model deployment Deep understanding of modern data stacks such as Spark, Databricks or cloud-native architectures Solid understanding of modern frontend engineering, DevOps knowledge and experience delivering machine learning systems Strong communication, organisation and stakeholder ...