26 to 50 of 177 Apache Spark Jobs in London

/Starburst Enterprise/Galaxy administration and CLI operations Container Orchestration : Proven track record with Kubernetes/OpenShift in production environments Big Data Ecosystem : Strong background in Hadoop, Hive, Spark, and cloud platforms (AWS/Azure/GCP) Systems Architecture : Understanding of distributed systems, high availability, and fault-tolerant design Security Protocols : Experience with LDAP, Active Directory, OAuth2, and More ❯

/Starburst Enterprise/Galaxy administration and CLI operations Container Orchestration : Proven track record with Kubernetes/OpenShift in production environments Big Data Ecosystem : Strong background in Hadoop, Hive, Spark, and cloud platforms (AWS/Azure/GCP) Systems Architecture : Understanding of distributed systems, high availability, and fault-tolerant design Security Protocols : Experience with LDAP, Active Directory, OAuth2, and More ❯

data modeling (star schema, snowflake schema). Version Control Practical experience with Git (branching, merging, pull requests). Preferred Qualifications (A Plus) Experience with a distributed computing framework like Apache Spark (using PySpark). Familiarity with cloud data services ( AWS S3/Redshift, Azure Data Lake/Synapse, or Google BigQuery/Cloud Storage ). Exposure to workflow … orchestration tools ( Apache Airflow, Prefect, or Dagster ). Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field. More ❯

data modeling (star schema, snowflake schema). Version Control Practical experience with Git (branching, merging, pull requests). Preferred Qualifications (A Plus) Experience with a distributed computing framework like Apache Spark (using PySpark). Familiarity with cloud data services ( AWS S3/Redshift, Azure Data Lake/Synapse, or Google BigQuery/Cloud Storage ). Exposure to workflow … orchestration tools ( Apache Airflow, Prefect, or Dagster ). Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field. More ❯

of data modelling and data warehousing concepts Familiarity with version control systems, particularly Git Desirable Skills: Experience with infrastructure as code tools such as Terraform or CloudFormation Exposure to Apache Spark for distributed data processing Familiarity with workflow orchestration tools such as Airflow or AWS Step Functions Understanding of containerisation using Docker Experience with CI/CD pipelines More ❯

of data modelling and data warehousing concepts Familiarity with version control systems, particularly Git Desirable Skills: Experience with infrastructure as code tools such as Terraform or CloudFormation Exposure to Apache Spark for distributed data processing Familiarity with workflow orchestration tools such as Airflow or AWS Step Functions Understanding of containerisation using Docker Experience with CI/CD pipelines More ❯

and delivering end-to-end AI/ML projects. Nice to Have: Exposure to LLMs (Large Language Models), generative AI , or transformer architectures . Experience with data engineering tools (Spark, Airflow, Snowflake). Prior experience in fintech, healthtech, or similar domains is a plus. More ❯

observability. Preferred Qualifications Exposure to machine learning workflows, model lifecycle management, or data engineering platforms. Experience with distributed systems, event-driven architectures (e.g., Kafka), and big data platforms (e.g., Spark, Databricks). Familiarity with banking or financial domain use cases, including data governance and compliance-focused development. Knowledge of platform security, monitoring, and resilient architecture patterns. About us More ❯

Science, Computer Science, or a related field. 5+ years of experience in data engineering and data quality. Strong proficiency in Python/Java, SQL, and data processing frameworks including Apache Spark. Knowledge of machine learning and its data requirements. Attention to detail and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a More ❯

Science, Computer Science, or a related field. 5+ years of experience in data engineering and data quality. Strong proficiency in Python/Java, SQL, and data processing frameworks including Apache Spark. Knowledge of machine learning and its data requirements. Attention to detail and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a More ❯

Science, Computer Science, or a related field. 5+ years of experience in data engineering and data quality. Strong proficiency in Python/Java, SQL, and data processing frameworks including Apache Spark. Knowledge of machine learning and its data requirements. Attention to detail and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a More ❯

Science, Computer Science, or a related field. 5+ years of experience in data engineering and data quality. Strong proficiency in Python/Java, SQL, and data processing frameworks including Apache Spark. Knowledge of machine learning and its data requirements. Attention to detail and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a More ❯

Python and SQL Hands-on experiences with Data Architecture, including: Cloud platforms and orchestration tools (e.g. Dagster, Airflow) AI/MLOps: Model deployment, monitoring, lifecycle management. Big Data Processing: Spark, Databricks, or similar. Bonus: Knowledge Graph engineering, graph databases, ontologies. Located in London And ideally you... Are a zero-to-one builder who thrives on autonomy and ambiguity. Are More ❯

Python and SQL Hands-on experiences with Data Architecture, including: Cloud platforms and orchestration tools (e.g. Dagster, Airflow) AI/MLOps: Model deployment, monitoring, lifecycle management. Big Data Processing: Spark, Databricks, or similar. Bonus: Knowledge Graph engineering, graph databases, ontologies. Located in London And ideally you... Are a zero-to-one builder who thrives on autonomy and ambiguity. Are More ❯

Python and SQL Hands-on experiences with Data Architecture, including: Cloud platforms and orchestration tools (e.g. Dagster, Airflow) AI/MLOps: Model deployment, monitoring, lifecycle management. Big Data Processing: Spark, Databricks, or similar. Bonus: Knowledge Graph engineering, graph databases, ontologies. Located in London And ideally you... Are a zero-to-one builder who thrives on autonomy and ambiguity. Are More ❯

Python and SQL Hands-on experiences with Data Architecture, including: Cloud platforms and orchestration tools (e.g. Dagster, Airflow) AI/MLOps: Model deployment, monitoring, lifecycle management. Big Data Processing: Spark, Databricks, or similar. Bonus: Knowledge Graph engineering, graph databases, ontologies. Located in London And ideally you... Are a zero-to-one builder who thrives on autonomy and ambiguity. Are More ❯

scalable pipelines, data platforms, and integrations, while ensuring solutions meet regulatory standards and align with architectural best practices. Key Responsibilities: Build and optimise scalable data pipelines using Databricks and Apache Spark (PySpark). Ensure performance, scalability, and compliance (GxP and other standards). Collaborate on requirements, design, and backlog refinement. Promote engineering best practices including CI/CD … experience: Experience with efficient, reliable data pipelines that improve time-to-insight. Knowledge of secure, auditable, and compliant data workflows. Know how on optimising performance and reducing costs through Spark and Databricks tuning. Be able to create reusable, well-documented tools enabling collaboration across teams. A culture of engineering excellence driven by mentoring and high-quality practices. Preferred Experience … Databricks in a SaaS environment, Spark, Python, and database technologies. Event-driven and distributed systems (Kafka, AWS SNS/SQS, Java, Python). Data Governance, Data Lakehouse/Data Intelligence platforms. AI software delivery and AI data preparation. More ❯

scalable pipelines, data platforms, and integrations, while ensuring solutions meet regulatory standards and align with architectural best practices. Key Responsibilities: Build and optimise scalable data pipelines using Databricks and Apache Spark (PySpark). Ensure performance, scalability, and compliance (GxP and other standards). Collaborate on requirements, design, and backlog refinement. Promote engineering best practices including CI/CD … experience: Experience with efficient, reliable data pipelines that improve time-to-insight. Knowledge of secure, auditable, and compliant data workflows. Know how on optimising performance and reducing costs through Spark and Databricks tuning. Be able to create reusable, well-documented tools enabling collaboration across teams. A culture of engineering excellence driven by mentoring and high-quality practices. Preferred Experience … Databricks in a SaaS environment, Spark, Python, and database technologies. Event-driven and distributed systems (Kafka, AWS SNS/SQS, Java, Python). Data Governance, Data Lakehouse/Data Intelligence platforms. AI software delivery and AI data preparation. More ❯

scalable pipelines, data platforms, and integrations, while ensuring solutions meet regulatory standards and align with architectural best practices. Key Responsibilities: Build and optimise scalable data pipelines using Databricks and Apache Spark (PySpark). Ensure performance, scalability, and compliance (GxP and other standards). Collaborate on requirements, design, and backlog refinement. Promote engineering best practices including CI/CD … experience: Experience with efficient, reliable data pipelines that improve time-to-insight. Knowledge of secure, auditable, and compliant data workflows. Know how on optimising performance and reducing costs through Spark and Databricks tuning. Be able to create reusable, well-documented tools enabling collaboration across teams. A culture of engineering excellence driven by mentoring and high-quality practices. Preferred Experience … Databricks in a SaaS environment, Spark, Python, and database technologies. Event-driven and distributed systems (Kafka, AWS SNS/SQS, Java, Python). Data Governance, Data Lakehouse/Data Intelligence platforms. AI software delivery and AI data preparation. More ❯

scalable pipelines, data platforms, and integrations, while ensuring solutions meet regulatory standards and align with architectural best practices. Key Responsibilities: Build and optimise scalable data pipelines using Databricks and Apache Spark (PySpark). Ensure performance, scalability, and compliance (GxP and other standards). Collaborate on requirements, design, and backlog refinement. Promote engineering best practices including CI/CD … experience: Experience with efficient, reliable data pipelines that improve time-to-insight. Knowledge of secure, auditable, and compliant data workflows. Know how on optimising performance and reducing costs through Spark and Databricks tuning. Be able to create reusable, well-documented tools enabling collaboration across teams. A culture of engineering excellence driven by mentoring and high-quality practices. Preferred Experience … Databricks in a SaaS environment, Spark, Python, and database technologies. Event-driven and distributed systems (Kafka, AWS SNS/SQS, Java, Python). Data Governance, Data Lakehouse/Data Intelligence platforms. AI software delivery and AI data preparation. More ❯

data modelling techniques + data integration patterns. Experience of working with complex data pipelines, large data sets, data pipeline optimization + data architecture design. Implementing complex data transformations using Spark, PySpark or Scala + working with SQL/MySQL databases. Experience with data quality, data governance processes, Git version control + Agile development environments. Azure Data Engineer certification preferred More ❯

GCP including BigQuery, Pub/Sub, Cloud Composer and IAM You have strong Python, SQL and PySpark skills You have experience with real-time data streaming using Kafka or Spark You have a good knowledge of Data Lakes, Data Warehousing, Data Modelling You're familiar with DevOps principles, containerisation and CI/CD tools such as Jenkins or GitHub More ❯

GCP including BigQuery, Pub/Sub, Cloud Composer and IAM You have strong Python, SQL and PySpark skills You have experience with real-time data streaming using Kafka or Spark You have a good knowledge of Data Lakes, Data Warehousing, Data Modelling You're familiar with DevOps principles, containerisation and CI/CD tools such as Jenkins or GitHub More ❯

GCP including BigQuery, Pub/Sub, Cloud Composer and IAM You have strong Python, SQL and PySpark skills You have experience with real-time data streaming using Kafka or Spark You have a good knowledge of Data Lakes, Data Warehousing, Data Modelling You're familiar with DevOps principles, containerisation and CI/CD tools such as Jenkins or GitHub More ❯

data reliability, scalability, and performance across the platform 🧩 The Tech Environment You’ll likely be working with some combination of: Languages: Python, Scala, Go Streaming: Kafka/Flink/Spark Structured Streaming Workflow orchestration: Airflow/Prefect/Dagster Data storage & processing: Snowflake/Detabricks/BigQuery/Redshift Infrastructure: Docker/Kubernetes/Terraform/dbt Monitoring: Prometheus More ❯