51 to 75 of 75 Apache Spark Jobs in London

containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute ...

containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute ...

containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute ...

containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute ...

operational processes Required Qualifications 3+ years of experience as a Data Engineer or in a similar role Strong experience with Azure Databricks (PySpark, Spark SQL) Hands-on experience with Azure Synapse Analytics (dedicated and/or serverless pools) Solid understanding of data warehousing concepts and dimensional modeling Proficiency … Experience working in Agile/Scrum environments Preferred Qualifications Azure certifications (e.g., Azure Data Engineer Associate ) Experience with streaming technologies (Event Hubs, Kafka, or Spark Structured Streaming) Knowledge of data governance tools (Purview, Unity Catalog) Experience with Power BI or other BI/analytics tools Exposure to DevOps, Infrastructure ...

operational processes Required Qualifications 3+ years of experience as a Data Engineer or in a similar role Strong experience with Azure Databricks (PySpark, Spark SQL) Hands-on experience with Azure Synapse Analytics (dedicated and/or serverless pools) Solid understanding of data warehousing concepts and dimensional modeling Proficiency … Experience working in Agile/Scrum environments Preferred Qualifications Azure certifications (e.g., Azure Data Engineer Associate ) Experience with streaming technologies (Event Hubs, Kafka, or Spark Structured Streaming) Knowledge of data governance tools (Purview, Unity Catalog) Experience with Power BI or other BI/analytics tools Exposure to DevOps, Infrastructure ...

data models and outputs Set up monitoring and ensure data health for outputs What we are looking for Proficiency in Python, with experience in Apache Spark and PySpark Previous experience with data analytics softwares Ability to scope new integrations and translate user requirements into technical specifications What ...

data models and outputs Set up monitoring and ensure data health for outputs What we are looking for Proficiency in Python, with experience in Apache Spark and PySpark Previous experience with data analytics softwares Ability to scope new integrations and translate user requirements into technical specifications What ...

code, CI/CD best practices, and cloud platforms (AWS, GCP, or Azure). Experience with relational databases and data processing and query engines (Spark, Trino, or similar). Familiarity with monitoring, observability, and alerting systems for production ML (Prometheus, Grafana, Datadog, or equivalent). Understanding of ML concepts. ...

code, CI/CD best practices, and cloud platforms (AWS, GCP, or Azure). Experience with relational databases and data processing and query engines (Spark, Trino, or similar). Familiarity with monitoring, observability, and alerting systems for production ML (Prometheus, Grafana, Datadog, or equivalent). Understanding of ML concepts. ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Aker Systems was founded in 2017 by a team of experienced technology professionals who recognised an opportunity to provide highly secure enterprise data platforms to large organisations. We build and operate ground-breaking, ultra-secure ...

models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. ...

models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. ...

tooling and working with large transactional datasets • Understanding of OTC products including CDS, Interest Rate Swaps and Variance Swaps Highly Desirable • Experience with C++, Spark, Kafka or other distributed compute tools • Exposure to position keeping, risk, or PnL systems • Strong debugging, profiling and optimisation capability across data pipelines ...

tooling and working with large transactional datasets Understanding of OTC products including CDS, Interest Rate Swaps and Variance Swaps Highly Desirable Experience with C++, Spark, Kafka or other distributed compute tools Exposure to position keeping, risk, or PnL systems Strong debugging, profiling and optimisation capability across data pipelines ...

Level grades are included on your CV). Basic scripting knowledge in Python or Bash Excellent customer-facing skills You have a sales spark - while this role isn't a focussed sales role, this is required due to the nature of the role A motivated self-starter with ...

platform design on Azure Databricks with Unity Catalog , ensuring scalability, governance, and performance. Develop, optimize, and maintain data pipelines using dbt, Delta Live Tables, Spark, and Delta Lake . Design and implement insurance data models , particularly for: Claims (paid, incurred, case reserves) Exposures and reference data Actuarial reserving … data transformation roadmap. Required Skills & Experience Strong background in data architecture and data engineering on Azure Databricks . Deep hands-on expertise with: Spark, Delta Lake, Unity Catalog dbt, Delta Live Tables, Prefect Azure DevOps CI/CD pipelines Solid understanding of actuarial and insurance data structures , including claims ...

platform design on Azure Databricks with Unity Catalog , ensuring scalability, governance, and performance. Develop, optimize, and maintain data pipelines using dbt, Delta Live Tables, Spark, and Delta Lake . Design and implement insurance data models , particularly for: Claims (paid, incurred, case reserves) Exposures and reference data Actuarial reserving … data transformation roadmap. Required Skills & Experience Strong background in data architecture and data engineering on Azure Databricks . Deep hands-on expertise with: Spark, Delta Lake, Unity Catalog dbt, Delta Live Tables, Prefect Azure DevOps CI/CD pipelines Solid understanding of actuarial and insurance data structures , including claims ...

generative AI applications. Perform Exploratory Data Analysis (EDA), data mining, and visualization to extract insights. Design and implement Big Data solutions using Hadoop, Spark, PySpark, and Data Lake architectures. Develop and deploy ML models (supervised, unsupervised, tree-based, ensemble methods). Implement deep learning architectures (CNN, RNN, LSTM) using … compliance of AI systems. Required Skills: Analytical Tools: EDA, Data Mining, Visualization (Plotly, Matplotlib, Seaborn) Statistical & Multivariate Analysis Big Data: Hadoop, MapReduce, HDFS, DataBricks, Spark, PySpark DataLake Architecture, AWS Redshift, Kinesis, EMR Machine Learning Supervised Models: Nave Bayes, Logistic Regression, SVM, Linear Regression, KNN, Tree-Based Models: Decision Trees ...