1 to 25 of 43 Apache Spark Jobs in London

code. Perfect if you want scope for growth without going “post-technical.” What you’ll do Design and build modern data platforms using Databricks, Apache Spark, Snowflake, and cloud-native services (AWS, Azure, or GCP). Develop robust pipelines for real-time and batch data ingestion from diverse … Lead Data Engineer in complex enterprise environments. Can demonstrate strong coding skills in Python (Scala or functional languages a plus). Expertise with Databricks, Apache Spark, and Snowflake is a must (HDFS/HBase also useful). Has experience integrating large, messy datasets into reliable, scalable data products. ...

Data Engineer, working with large-scale, complex datasets in regulated environments Scala development experience supporting analytics or data-processing solutions Hands-on experience with Apache Spark for large-scale distributed data processing Experience with model calibration, threshold management, and score explainability to meet AML governance and regulatory standards … Analyst or Data Engineer, working with large, complex datasets in regulated environments Solid Scala development experience, writing and supporting scalable data and analytics solutions Apache Spark experience, including batch and/or dynamic processing of high-volume data About Us FDM is an award-winning global leader ...

data engineering tasks. Experience with cloud platforms such as: AWS, Azure, Google Cloud Platform (GCP) Hands-on experience with data technologies such as: Apache Spark, Databricks, Kafka, Airflow, Snowflake, Hadoop ecosystems Experience designing and maintaining data warehouses and data lakes. Knowledge of DevOps and CI/CD tooling ...

Experience with Airflow for orchestration. p]:pt-0 [&>p]:mb-2 [&>p]:my-0'> Exposure to big data frameworks such as Spark, Hadoop, or Presto. p]:pt-0 [&>p]:mb-2 [&>p]:my-0'> Experience supporting AI/ML data pipelines. ...

understand where traditional patterns remain appropriate - and where modern approaches add measurable value. Data Engineering & Platform Understanding: Strong knowledge of distributed processing (e.g. Apache Spark). Familiarity with Hadoop ecosystem components. Working knowledge of SQL and NoSQL technologies. Understanding of ETL/ELT design trade-offs. Awareness ...

Collaborate with senior developers and quantitative teams on new analytics capabilities Participate in debugging, testing, and production support activities Technology Environment Python Databricks/Apache Spark SQL Pandas/NumPy Git REST APIs Cloud technologies (Azure or AWS) Numerix (or equivalent pricing/risk platform) Jupyter/notebook … commercial Python development experience Strong understanding of data structures and software engineering fundamentals Experience working with data engineering or analytics tooling Exposure to Databricks, Spark, or cloud-based data platforms Understanding of SQL and relational databases Excellent problem-solving and communication skills STEM or Computer Science degree preferred Nice ...

improving patient outcomes through reliable and scalable machine learning systems. Key Responsibilities ML Pipeline Orchestration & Automation Own and extend ML pipeline orchestration workflows using Apache Airflow, including training, evaluation, and deployment workflows. Build and maintain automated pipelines for model retraining, validation, and promotion across development, staging, and production environments. … related infrastructure roles. Strong proficiency in Python for ML pipeline development, tooling, and automation. Hands-on experience with ML pipeline orchestration tools, particularly Apache Airflow. Experience with model registries and experiment tracking platforms such as MLflow. Experience deploying and operating ML workloads on AWS. Strong understanding ...

clouds (AWS, Azure, GCP) and cloud data warehousing solutions like Snowflake and Databricks. Certifications with each are a plus. Understanding of SQL, Python, R, Apache Spark or similar product or language are also a plus.* Strong knowledge of data analytics, data science, ETL processes, AI/ML workflows ...

focus on production-quality code • Solid understanding of ETL processes and best practices • Experience with SQL/NoSQL databases and big data tools (e.g. Spark, Pulsar) • Hands-on experience with cloud platforms (AWS, Azure, or GCP) • Experience developing and deploying data services end-to-end • Strong stakeholder communication ...

focus on production-quality code • Solid understanding of ETL processes and best practices • Experience with SQL/NoSQL databases and big data tools (e.g. Spark, Pulsar) • Hands-on experience with cloud platforms (AWS, Azure, or GCP) • Experience developing and deploying data services end-to-end • Strong stakeholder communication ...

focus on production-quality code • Solid understanding of ETL processes and best practices • Experience with SQL/NoSQL databases and big data tools (e.g. Spark, Pulsar) • Hands-on experience with cloud platforms (AWS, Azure, or GCP) • Experience developing and deploying data services end-to-end • Strong stakeholder communication ...

capacity planning, skills development, and vendor contributions The individual: Expertise in Azure data services (ADLS, ADF, Databricks, Synapse, Event Hub/Kafka), Python, SQL, Spark/PySpark. Experience with data modeling, metadata and lineage tooling; performance & cost optimization. Proven leadership in engineering teams; Agile/DevOps ways of working ...

Strong SQL skills for data validation, reconciliation, and analysis. Experience working with data warehouses, data lakes, or big data platforms (e.g., Snowflake, Redshift, BigQuery, Spark). Familiarity with integrating automated tests into CI/CD pipelines (e.g., Jenkins, Azure DevOps, GitHub Actions, GitLab CI). Familiarity with version control ...

strong focus on scalability, resilience, and performance. Develop and optimise scalable data pipelines , supporting both batch and streaming workloads, using technologies such as Apache Spark . Work extensively with data technologies , leveraging Python and SQL to deliver high-quality analytical and data-driven solutions. Lead the design ...

experience with SQL and data modelling concepts Strong analytical and problem-solving skills Nice to Have Skills Experience with data pipeline tools (Airflow, Kafka, Spark) Knowledge of cloud platforms (AWS, Azure or GCP) Familiarity with relational and NoSQL databases Additional programming experience (Python, Scala) Essential Requirements Active SC Clearance ...

multiples sources (APIs, BDD, streams, fichiers). Qualité, Performance & Fiabilité Déployer des mécanismes de Data Quality (contrôles, monitoring, alerting). Optimiser les traitements Spark (partitioning, tuning, formats de données). Assurer la supervision et la résolution des incidents en production. CI/CD & Gouvernance Industrialiser les développements ...

batch data processing systems for voice compliance assurance Low‐latency record matching and reconciliation engines handling billions of events Scalable data services operating across Spark, Kafka, Hive and Hadoop Production‐grade pipelines supporting regulatory evidence, audit and controls Foundations for near‐real‐time compliance signal generation across global voice … platforms Key Responsibilities Design and develop high‐performance distributed systems for large‐scale voice data processing Build and optimise Spark‐based processing jobs for high‐volume and high‐frequency workloads Engineer Kafka‐based streaming pipelines with strong delivery guarantees and low end‐to‐end latency Develop robust data matching ...

Proficient SQL skills for data analysis, validation, and troubleshooting. Experience working with data warehouses, data lakes, or big data platforms (e.g., Snowflake, Redshift, BigQuery, Spark). Engineering Practices & Tooling Experience with CI/CD pipelines and automated build and deployment processes. Strong experience with version control systems (Git). ...

Proficient SQL skills for data analysis, validation, and troubleshooting. Experience working with data warehouses, data lakes, or big data platforms (e.g., Snowflake, Redshift, BigQuery, Spark). Engineering Practices & Tooling Experience with CI/CD pipelines and automated build and deployment processes. Strong experience with version control systems (Git). ...

Cloud engineering: Azure (preferred) and/or AWS/GCP; Kubernetes/Docker; serverless (Azure Functions/Lambda); secure networking/IAM. Data engineering: Spark/Databricks, ETL/ELT pipelines; integration with client data sources and enterprise systems; runbooks and operational handover. Product delivery: workshop facilitation, PRDs, user ...

internal knowledge Competencies and Behaviours: 3+ years experience in data platform engineering, cloud engineering, or similar roles Strong hands-on experience with Databricks, including Apache Spark, Delta Lake, Workflows Proven experience designing and deploying data platforms on AWS and/or Azure (e.g. ADLS, S3, VNet/ ...

bring: Strong SQL + ETL/ELT experience Knowledge of Python/T-SQL Exposure to cloud platforms (Azure preferred) Nice to have: Databricks, Spark, CI/CD, big data This is a great opportunity to join a high-impact data team in a global organisation and shape ...

Azure Key Vault, Azure Monitor, Azure Log Analytics, Azure API Management (APIM), Azure DevOps. Databases : SQL Server, Oracle, PostgreSQL, Delta Lake Big Data : Apache Spark Version Control : GitHub, Git, Azure DevOps Visualization : Power BI & Integration with REST APIs for custom dashboards. Data Integration & Workflow Orchestration : Azure Data Factory ...

learning frameworks (TensorFlow, PyTorch, Keras) Knowledge of prompt engineering, RAG (Retrieval Augmented Generation), and LLM fine‐tuning techniques Familiarity with distributed computing frameworks (eg Spark) Knowledge of graph neural networks, reinforcement learning, or causal inference Experience with AI governance, model risk management, and regulatory compliance Experience using Pro code ...

optimization. Strong experience with Time Series Forecasting, Sequence Modelling, Signal Processing or Quantitive Analysis Proficient in Python and SQL. Experience with frameworks like PyTorch, Spark, or Airflow is highly desirable. Familiarity with AWS (SageMaker, Lambda) and CI/CD automation. Strong understanding of MLOps, data versioning, and quality management ...