6 of 6 Apache Spark Jobs in the Thames Valley

with strong Foundry depth). Proven, hands-on experience working with Palantir Foundry in a production environment. Strong proficiency in Python, SQL, PySpark and Spark SQL Experience delivering production pipelines in AWS, Azure, or GCP environments. Solid understanding of data modeling, schema design, metadata management, and governance. Familiarity with ...

experience working with Data A strong understanding of data integration techniques and solution/performance optimisation Excellent understanding and knowledge of SQL, Python or Spark Apply relevant data modelling techniques (e.g. STAR, Snowflake) Excellent Communication and Teamwork Skills Coaching and mentoring experience Technologies & Experience Desired: Git and JIRA software ...

skills in Python, and experience with Java or Scala. Data Engineering at Scale: Solid ELT/ETL design experience and hands-on work with Apache Spark. Bonus points if you have: Multi-Cloud Exposure: Experience with Azure alongside GCP. Container Orchestration: Experience packaging and deploying workloads with Helm ...

Scale processing across distributed cloud warehouses/storage via container orchestration (e.g. Kubernetes), High-Performance GPU Compute (e.g. Slurm), or distributed compute frameworks (e.g. Spark, Ray). Contribute to an engineering culture that values maintainability, testing, robust system design, and deep collaboration, but allows flexibility for rapid prototyping ...

model validation. Experiment tracking and reproducibility tools, for example MLflow, Weights & Biases or equivalent. Data wrangling and analysis using Pandas, NumPy, SQL; familiarity with Spark or similar is a plus. Model optimisation and research-to-prototype deployment fundamentals, including ONNX, TorchScript, FastAPI/gRPC and GPU acceleration, with CUDA ...

engineering practices to multi-disciplinary teams. Desirable Skills, Qualifications & Experience: Experience leveraging Kubernetes for application deployment, and familiarity with distributed computing frameworks (e.g., Ray, Spark), or specialised batch schedulers/resource managers (e.g., Slurm, Volcano, Kueue). Demonstratedexpertisewith specialised serving engines (e.g.,vLLM,SGLang) or techniques for deploying models ...