17 of 17 Apache Spark Jobs in Central London

root‐cause analysis. Experience building or supporting production data pipelines in a collaborative engineering environment. Experience working with distributed data processing frameworks such as Apache Spark . Working knowledge of common data formats such as JSON , Avro and Parquet . Technology Environment The role will involve working with … should bring relevant experience and the ability to work across comparable technologies. Examples of technologies in scope include: Data processing and logic: ANSI SQL, Apache Spark, Kafka Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ Engineering and deployment: CI/CD tooling, containerised ...

will be undertaking a monumental Transformation to unlock organisational pace and Data agility, moving to a scalable Cloud Data architecture centred around AWS Glue (Apache Spark) & Apache Airflow, with a key focus on re-engineering numerous complex Data pipelines to the new framework by leveraging Agentic … code generation in regulated environments Strong hands-on experience with AWS ecosystem: AWS Glue, S3, and related data platforms (e.g. Snowflake) Strong experience with Apache Airflow and DAG-based orchestration Experience designing configuration-driven frameworks: Using YAML or JSON Experience building automated testing for data pipelines: Functional equivalence testing ...

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 ...

models are always running, always accurate, and always improving. Key Responsibilities ML Pipeline Orchestration & Automation Own and extend Circadia’s ML pipeline orchestration 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. … closely related infrastructure role. 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 (MLflow preferred). Experience deploying and operating ML workloads on AWS (Batch ...

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 ...

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 ...

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 ...

Docker and Kubernetes is a plus. Experience designing end to end ML data pipelines. Experience with database technologies such as PostgreSQL, MySQL, or MongoDB, Spark, Databricks and stream data processing such as Kafka, RedPanda is a plus. Direct experience in building and applying large-scale (100M+ users) machine learning ...

spanning model development through to data engineering Comfortable working across major cloud platforms (Azure, AWS or GCP) with hands-on exposure to tools like Spark, Hive or Redshift A track record of leading cross-functional teams and communicating technical concepts to non-technical audiences Experience with MLOps practices ...

ideal candidate will have a strong programming background in Python or Java, knowledge of SQL, and experience with data processing frameworks such as Apache Spark. Responsibilities include enhancing data pipelines, ensuring data quality, and collaborating with engineering teams. The position is located in London and offers significant growth opportunities ...

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 ...

business stakeholders to deliver robust, high-performance data solutions in a cloud-native AWS environment. The ideal candidate has strong expertise in PySpark, Python, Apache Airflow, AWS services, Terraform, and modern DevOps practices. Good to have SC eligibility or SC clearance Key Responsibilities Data Engineering & Pipeline Development Design, develop … transformation, cleansing, enrichment, and validation processes. Troubleshoot and resolve data pipeline failures, bottlenecks, and performance issues. Workflow Orchestration Design and manage complex workflows using Apache Airflow. Create and maintain DAGs with robust scheduling, dependency management, alerting, and recovery mechanisms. Monitor workflow execution and proactively address failures or performance concerns. ...

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 ...

with Git, Python, and Ansible Familiarity with containers (Docker, Kubernetes, LXC) Experience with monitoring tools and SQL databases Exposure to big data systems (e.g., Spark, HDFS, Airflow) Summary A great opportunity for someone who enjoys solving complex infrastructure challenges, automating systems, and working closely with engineering teams. Spectrum ...

work on a Big Data Project in the finance sector. Required Experience: Java Big Data experience On-premises cluster experience Databases Kubernetes Kafka Apache Spark Preffered Experience: Finance sector experience ...

work on a Big Data Project in the finance sector. Required Experience: Java Big Data experience On-premises cluster experience Databases Kubernetes Kafka Apache Spark Preffered Experience: Finance sector experience ...

Strong SQL and database knowledge Experience working with large-scale or high-volume datasets Exposure to big data or distributed systems technologies such as Spark or Kafka Previous experience within financial services is beneficial but not essential Strong academic background, ideally in Computer Science What ...