51 to 75 of 124 Apache Spark Jobs in England

grade ML workflows. Experience designing CI/CD pipelines using Azure DevOps, GitHub Actions or similar tools. Advanced Python skills, with knowledge of SQL, Spark and testing approaches for ML. Understanding of data engineering concepts such as ETL/ELT, feature stores and lineage tracking. Awareness of security, governance ...

auction systems Excellent communication skills, able to explain complex technical systems to commercial, operations and senior leadership teams. Experience with Google Cloud, Docker, Kafka, Spark, Airflow, ElasticSearch, ClickHouse or similar production infrastructure Experience owning product roadmaps, release governance or cross-functional delivery across distributed teams and time zones. What ...

isolation, Kubernetes/container orchestration, serverless patterns. Working knowledge of cloud data platforms (Snowflake, Databricks, BigQuery, Azure Synapse) and real-time streaming (Kafka, Flink, Spark Streaming). Familiarity with generative AI patterns (LLM fine-tuning, RAG, prompt engineering, function calling, agent frameworks) and graph/knowledge graph technologies. DevOps ...

such as MLflow, Airflow, model monitoring, API monitoring, data validation, data drift detection, autoscaling and access management. Strong Python experience, with helpful knowledge of Spark or PySpark for working with large‐scale data and machine learning systems. An understanding of feature stores and related data technologies used to support ...

source models or integrating with managed foundation model platforms. Hands-on experience building data pipelines and model workflows using tools such as Python, SQL, Spark or similar data processing technologies. Experience deploying and operating AI systems in cloud environments using containerisation, managed ML services or serverless architectures. Understanding ...

Company Description Publicis Media harnesses the power of modern media through leading agency brands Dysrupt, Infinite Roar, Publicis Collective, Publicis Health Media, Spark Foundry, Starcom, and Zenith, as well as global accelerator PMX; immersive experience group PMCI and access to integrated platform‐based technologies and offerings from CJ, Epsilon ...

ownership.Experience designing and enforcing data contracts and quality SLAs in distributed data ecosystems.Proficiency in Python, Java, or Scala, and experience building pipelines with Databricks, Spark, or Kafka.Strong understanding of data governance principles, privacy regulations (GDPR, CCPA), and secure data handling practices.Familiarity with metadata management and data catalog tools (e.g.DataHub ...

foundation models, embeddings, vector databases, RAG architectures, and agentic AI systems. Experience working with large-scale datasets using SQL, distributed processing platforms such as Spark, and cloud-based infrastructure. Strong communication and data visualisation skills, with the ability to explain complex technical concepts to technical and non-technical audiences. ...

platforms that enable real‐time and batch data processing at scale. Responsibilities Drive platform capability improvements – continuously enhance distributed data platforms using knowledge of Spark, Databricks, Kafka, Pulsar, Cassandra, and object stores to maintain best‐in‐class capabilities. Enable application data consumption – understand how applications produce and consume data … structures, partitioning strategies, consistency models, and performance optimisation, as well as OLTP databases such as PostgreSQL and MySQL. Distributed compute frameworks – strong experience with Apache Spark and distributed data processing, including optimisation, performance tuning, and large‐scale batch/streaming workloads. Cloud‐native data platforms – demonstrated experience with ...

security controls. Monitor, maintain and optimise data platforms to ensure performance and reliability. Skills and Experience Required: ETL development using Python or similar languages Apache Spark, NiFi, or Kafka Relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra) databases AWS and cloud-based data services Palantir Foundry Stakeholder Engagement ...

including data modelling, DAX and semantic model design Hands-on experience with Microsoft Fabric, particularly lakehouse architecture, notebooks and data pipelines Strong understanding of Apache Spark/PySpark and large-scale data processing Experience designing and operating modern data platforms Experience developing or enabling AI and machine learning ...

Integrating data platforms with AI and agent-based applications Deploying services in secure cloud and containerised environments What they're looking for Strong Python Spark/PySpark Kafka, Flink, Iceberg and Trino Data modelling, lineage and provenance Knowledge graphs and entity resolution AWS or Azure Docker and Kubernetes Experience ...

teams to drive outcomes Core skills (indicative) Production pipeline design and deployment experience Strong engineering capability with Python, SQL, plus big data tooling (e.g., Spark, and Java/Scala where relevant AWS, Azure, GCP Working pattern Hybrid working, with the team on client site or in the office ...

experience in software engineering, MLOps, and deploying machine learning models at scale. Proficiency in SQL, Python, and familiarity with big data technologies (e.g., Kafka, Spark) and/or cloud platforms (e.g., GCP, AWS, or Azure). Industry knowledge: Experience in gaming or digital entertainment is a strong plus. ...

/CD) practices Useful skills: Working knowledge of using GEN AI tools for coding Experience with Python/Scala or big data frameworks (e.g. spark) or Batch Processing. Working knowledge or certifications relevant to public cloud, preferably AWS. Experience with any of streaming, messaging, event bus technologies while building ...

partner management and ability to influence across teams and organisations. Continuous learning and improvement mentality. Desired Experience with big data technologies (e.g. Hadoop, Hive, Spark). Experience with generative AI, LLMs, or retrieval-augmented generation (RAG). Exposure to Agentic AI concepts, including autonomous agents, tool use, and orchestration ...

Applying advanced techniques in LLMs, agentic systems, vector databases, fine‐tuning, and deployment tools (e.g., HuggingFace, Langchain). Hands‐on experience working with Distributed Spark based systems Experience with data engineering concepts or a good understanding of data engineering concepts Pre-sales or post-sales experience working with external … clients across a variety of industry markets. Minimum of 5+ years of customer‐facing experience would be preferred Preferred: Experience working with Apache Spark (TM) to process large‐scale distributed datasets Communication: Proven ability to communicate and teach complex technical concepts to both technical and non‐technical audiences. ...

rather than “telling”, preferring to inspire stakeholders through built examples. Technical Expertise: Deep experience in core data & AI technologies, including languages (Python, SQL), frameworks (Apache Spark) and platforms (Databricks, etc.) Collaboration: You can orchestrate diverse teams to achieve a common goal and explain complex tech to non-technical ...

Experience with Infrastructure-as-Code tools such as Terraform Knowledge of DevOps, CI/CD, platform automation, and cloud‐native operational practices Familiarity with Apache Spark, dbt, and modern data integration technologies Delivery Experience Experience leading architecture for enterprise-wide Databricks implementations and cloud data modernization initiatives Proven ...

Nice to have: Experience with CI/CD pipelines (GitLab, Jenkins) Exposure to data tooling (Airflow, NiFi, Elasticsearch) Experience with Cloudera/Hadoop ecosystems (Spark, Hive, HDFS) Why join? Work on modern data platforms at scale Collaborate with data scientists and engineering teams Opportunity to shape platform architecture ...

platforms (AWS, Azure, or GCP). Distributed Systems Mastery: Deep technical capability in structuring data platforms, data pipelines, and high‐throughput distributed systems (like Spark or Kafka) optimized for performance and scalability. Cross‐Functional Technical Leadership: Exceptional ability to bridge the gap between deep technical engineering and strategic business ...

platforms (AWS, Azure, or GCP). Distributed Systems Mastery: Deep technical capability in structuring data platforms, data pipelines, and high‐throughput distributed systems (like Spark or Kafka) optimized for performance and scalability. Cross‐Functional Technical Leadership: Exceptional ability to bridge the gap between deep technical engineering and strategic business ...

scalable data analytical solutions in a large-scale business environment Experience in deep analytic focused work leveraging Distributed File System ecosystem tools: Linux, Python, Spark, Hive; and modern data platforms and tools (e.g. Databricks, NoSQL stores) and AI/ML frameworks (e.g. NLP). LLM integration patterns, RAG pipelines ...

batch processing, and scalable enterprise workloads, integrating with clients' incumbent technology estates. Implement hybrid-cloud and multi-cloud strategies using modern data infrastructure (Kafka, Spark, data lakes), MLOps practices, and deployment platforms. Ensure compliance with data privacy regulations (including UK GDPR) and responsible AI standards, incorporating governance, observability ...

Strong experience with MLOps, production ML systems, model lifecycle management, and monitoring. Experience working with large-scale data systems and distributed computing frameworks (e.g. Spark, Hadoop). Knowledge of experimental design, scientific methodology, and analysis. Strong partner management and confirmed ability to influence large organisations without direct authority. Demonstrated ...