9 of 9 Permanent Apache Spark Jobs in Somerset

environments Owning the cloud infrastructure underpinning data systems through a DevOps approach Knowledge of handling and transforming various data types (JSON, CSV, etc) with Apache Spark, Databricks or Hadoop Good understanding of the possible architectures involved in modern data system design (e.g. Data Warehouse, Data Lakes and Data ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

analytics tools Familiarity with industry common BI and ETL solutions Hands-on experience in a technical role leveraging SQL, Python, Java and/or Spark to build, operate and maintain data analytics solutions Extensive knowledge of and experience with large-scale database technology (e.g. Snowflake, Netezza, Exadata, Teradata, Greenplum ...

PyTorch) into real customer value Working closely with engineering teams using TypeScript, Node.js, React, and Next.js Partnering with data teams working across AWS, Kafka, Spark, and modern data pipelines Shaping products built on secure, scalable fintech architecture (Event-driven, microservices, serverless) Running discovery experiments and validating concepts at speed ...

. • Experience building and deploying applications on Kubernetes (EKS). Ask anything Important skills: Must have: 1. Bash Scripting 2.Real time with Spark structured streaming Nice to have : Familiarity with IceBerg GCP/BQexposure ...

looking for an experienced Senior Data Engineer to assist with building and managing data pipelines using the Elastic Stack (Elasticsearch, Logstash, Kibana) and Apache NiFi Key Responsibilities: Design, develop, and maintain secure and scalable data pipelines using the Elastic Stack (Elasticsearch, Logstash, Kibana) and Apache NiFi. Implement data … Skillset: Experience working in government, defence, or highly regulated industries with knowledge of relevant standards. Experience with additional data processing and ETL tools like Apache Kafka, Spark, or Hadoop Familiarity with containerization and orchestration tools such as Docker and Kubernetes. Experience with monitoring and alerting tools such ...

HOLD DV CLEARANCE OUTSIDE IR35 This role requires strong expertise in building and managing data pipelines using the Elastic Stack (Elasticsearch, Logstash, Kibana) and Apache NiFi. The successful candidate will design, implement, and maintain scalable, secure data solutions, ensuring compliance with strict security standards and regulations. This … compressed hours. The role will include: Design, develop, and maintain secure and scalable data pipelines using the Elastic Stack (Elasticsearch, Logstash, Kibana) and Apache NiFi. Implement data ingestion, transformation, and integration processes, ensuring data quality and security. Collaborate with data architects and security teams to ensure compliance with security ...

fast-paced, challenging environment. Key Responsibilities: Design, implement, and debug ETL pipelines to process and manage complex datasets. Leverage big data tools, including Apache Kafka, Spark, and Airflow, to deliver scalable solutions. Collaborate with stakeholders to ensure data quality and alignment with business goals. Utilize programming expertise … experience in data engineering projects Good hands-on experience of designing, implementing, debugging ETL pipeline Expertise in Python, PySpark and SQL languages Expertise with Spark and Airflow Experience of designing data pipelines using cloud native services on AWS Extensive knowledge of AWS services like API Gateway, Lambda, Redshift, Glue ...

data. You'll work with engineering to move models from idea to production. Tech Stack: Python, scikit-learn, PyTorch, TensorFlow/Keras, LangChain, Pydantic, Spark, Kafka, Databricks, MLflow, Azure, Docker, Kubernetes. Salary: Up to £100k Working Environment: Fully Remote in UK What you'll do Research, prototype, and deploy … summarisation, document processing) Build and tune models using scikit-learn, PyTorch, TensorFlow/Keras, and XGBoost Create data pipelines for batch and streaming with Spark and Kafka Use Databricks and MLflow for experiments, deployment, and monitoring What you'll bring Hands-on Python for data science and ML Practical ...