4 of 4 Permanent Apache Spark Jobs in Surrey

data security, privacy, and compliance frameworks ● Exposure to machine learning pipelines, MLOps, or AI-driven data products ● Experience with big data platforms and technologies such as EMR, Databricks, Kafka, Spark ● Exposure to AI/ML concepts and collaboration with data science or AI teams. ● Experience integrating data solutions with AI/ML platforms or supporting AI-driven analytics More ❯

exposure to cloud-native data infrastructures (Databricks, Snowflake) especially in AWS environments is a plus Experience in building and maintaining batch and streaming data pipelines using Kafka, Airflow, or Spark Familiarity with governance frameworks, access controls (RBAC), and implementation of pseudonymisation and retention policies Exposure to enabling GenAI and ML workloads by preparing model-ready and vector-optimised datasets More ❯

Python data science stack Knowledge of OO programming, software design, i.e., SOLID principles, and testing practices. Knowledge and working experience of AGILE methodologies. Proficient with SQL. Familiarity with Databricks, Spark, geospatial data/modelling and insurance are a plus. Exposure to MLOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc are desirable 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. Collaborate on requirements, design, and backlog refinement. Promote engineering best practices including CI/CD, code reviews, and testing. Research … 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 ❯