26 to 50 of 76 Apache Spark Jobs in London

data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache SparkTM, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits ...

Experience designing and enforcing data contracts and quality SLAs in distributed data ecosystems. Proficiency in Python or Java, and experience building pipelines with Airflow, Spark, or Kafka. Strong understanding of data governance principles, privacy regulations (such as the GDPR, CCPA), and secure data handling practices. Familiarity with metadata management ...

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 ...

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 ...

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. ...

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 ...

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 ...

Databricks. Familiarity with cloud‐based application development (AWS & Azure). Familiarity with one or more ML frameworks and technologies: scikit‐learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, Triton. Strong communication skills, able to express ideas clearly and collaborate across teams. #J-18808-Ljbffr ...

Role : Senior Data Manager/Lead Location : London (Hybrid) Comp : £115,000 P/A (FTC) Duration: 12 Months Skills: Python (Programming Language), SQL, Apache Spark, PySpark, Azure Databricks, Data Lakes, Data Warehouse Architecture, Leadership, Software Development, Management The role We're partnering with a large, data-driven ...

audit trails are essential. Desirable Skills & Experience Databricks Certified Data Engineer Professional or equivalent Databricks certification. Experience with adjacent data tooling such as dbt, Apache Spark, or AWS Glue. Familiarity with data product management tooling and data marketplace patterns. Previous experience in a technology modernisation or platform migration ...

data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn, Facebook. Benefits At Databricks, we strive to provide comprehensive benefits ...

experience Term structure modelling, stochastic calculus or Monte Carlo methods Interest rate curve bootstrapping Algorithmic execution experience Data lake or warehouse experience (Snowflake, Iceberg, Spark etc.) We’re people without borders—without judgement or prejudice, too. We want to work with the best people, no matter their background. ...

Python and a solid understanding of software development lifecycle principles Experience in modular code, unit testing, regression testing, and distributed computing (e.g., MapReduce, Spark DataFrames) Proven track record of leading and executing enterprise‐wide initiatives Strong communicator able to explain complex methodologies to senior stakeholders, auditors and regulators Skills ...

with experience shaping technical direction across teams and stakeholders Solid expertise in relevant technologies such as AWS, Terraform, Kafka/MSK, Airflow, Glue or Spark, and building scalable data solutions Experience with modern data ecosystems including data lakes/lakehouse architectures, Iceberg or similar table formats, as well ...

with experience shaping technical direction across teams and stakeholders Solid expertise in relevant technologies such as AWS, Terraform, Kafka/MSK, Airflow, Glue or Spark, and building scalable data solutions Experience with modern data ecosystems including data lakes/lakehouse architectures, Iceberg or similar table formats, as well ...