1 to 25 of 40 Remote Apache Spark Jobs in the UK excluding London

Job Accountabilities Develop robust, scalable data pipelines to serve the easyJet analyst and data science community. Highly competent hands-on experience with relevant Data Engineering technologies, such as Databricks, Spark, Spark API, Python, SQL Server, Scala. Work with data scientists, machine learning engineers and DevOps engineers to develop, develop and deploy machine learning models and algorithms aimed at … indexing, partitioning. Hands-on IaC development experience with Terraform or CloudFormation. Understanding of ML development workflow and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data … e.g. access management, data privacy, handling of sensitive data (e.g. GDPR) Desirable Skills Experience in event-driven architecture, ingesting data in real time in a commercial production environment with Spark Streaming, Kafka, DLT or Beam. Understanding of the challenges faced in the design and development of a streaming data pipeline and the different options for processing unbounded data (pubsub More ❯

an AI Engineer, you will be responsible for designing and developing intelligent agents capable of autonomous decision-making in distributed environments. You will leverage your expertise in Python and Spark to process large-scale data and use modelling techniques to enable complex agentic behaviours. Experience working with MCP servers or similar distributed computing platforms is key. Key Responsibilities: Design … and develop agentic AI systems that operate autonomously across diverse data sources and workflows. Implement scalable data processing pipelines using Apache Spark and Python. Build, train, and fine-tune advanced AI/ML models for agent reasoning, planning, and execution. Integrate solutions with MCP (Massively Concurrent Processing) servers or equivalent architectures. Work closely with data engineers, researchers, and … Skills & Experience: 4+ years of experience in AI/ML engineering or data-intensive systems. Strong proficiency in Python for AI, ML, and data engineering tasks. Deep experience with Apache Spark (PySpark or Scala-based implementations). Solid understanding and hands-on experience with modelling intelligent agents, including symbolic, neural, or hybrid approaches. Experience deploying to and managing More ❯

field. Technical Skills Required • Hands-on software development experience with Python and experience with modern software development and release engineering practices (e.g. TDD, CI/CD). • Experience with Apache Spark or any other distributed data programming frameworks. • Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. • Experience with cloud infrastructure like AWS … Skills • Hands-on development experience in an airline, e-commerce or retail industry • Experience in event-driven architecture, ingesting data in real time in a commercial production environment with Spark Streaming, Kafka, DLT or Beam. • Experience implementing end-to-end monitoring, quality checks, lineage tracking and automated alerts to ensure reliable and trustworthy data across the platform. • Experience of More ❯

plus work experience BS & 5+ years of work experience MS & 4+ years of work experience Proficient with machine learning and statistics Proficient with Python, deep learning frameworks, Computer Vision, Spark Have produced production level algorithms Proficient in researching, developing, synthesizing new algorithms and techniques Excellent communication skills Desirable Qualifications Master's or PhD level degree 5+ years of work More ❯

driven decision-making. Responsibilities for the Senior Data Engineer: Design, build, and maintain scalable data pipelines and architectures, ensuring reliability, performance, and best-in-class engineering standards Leverage Databricks, Spark, and modern cloud platforms (Azure/AWS) to deliver clean, high-quality data for analytics and operational insights Lead by example on engineering excellence, mentoring junior engineers and driving … customer data Continuously improve existing systems, introducing new technologies and methodologies that enhance efficiency, scalability, and cost optimisation Essential Skills for the Senior Data Engineer: Proficient with Databricks and Apache Spark, including performance tuning and advanced concepts such as Delta Lake and streaming Strong programming skills in Python with experience in software engineering principles, version control, unit testing More ❯

platform. Candidate Profile: Proven experience as a Data Engineer, with strong expertise in designing and managing large-scale data systems. Hands-on proficiency with modern data technologies such as Spark, Kafka, Airflow, or dbt. Strong SQL skills and experience with cloud platforms (Azure preferred). Solid programming background in Python, Scala, or Java. Knowledge of data warehousing solutions (e.g. More ❯

Development Opportunities Enhanced Maternity & Paternity Charity Volunteer Days Cycle to work scheme And More.. DATA ENGINEER – ESSTENTIAL SKILLS Proven experience building data pipelines using Databricks . Strong understanding of Apache Spark (PySpark or Scala) and Structured Streaming . Experience working with Kafka (MSK) and handling real-time data . Good knowledge of Delta Lake/Delta Live Tables More ❯

skills, and the ability to think critically and analytically High experience in documentation and data dictionaries Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark Excellent communication skills to effectively collaborate with cross-functional teams and present insights to business stakeholders Please can you send me a copy of your CV if you're More ❯

having resided in the UK for at least the past 5 years and being a UK national or dual UK national. Experience in prominent languages such as Python, Scala, Spark, SQL. Experience working with any database technologies from an application programming perspective - Oracle, MySQL, Mongo DB etc. Experience with the design, build and maintenance of data pipelines and infrastructure More ❯

/ELT pipelines , data modeling , and data warehousing . Experience with cloud platforms (AWS, Azure, GCP) and tools like Snowflake, Databricks, or BigQuery . Familiarity with streaming technologies (Kafka, Spark Streaming, Flink) is a plus. Tools & Frameworks: Airflow, dbt, Prefect, CI/CD pipelines, Terraform. Mindset: Curious, data-obsessed, and driven to create meaningful business impact. Soft Skills: Excellent 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 ❯

version control, e.g., Git. 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 Exposure to MLOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc. are a plus. Additional Information What’s More ❯

for best practice and technical excellence and be a person that actively looks for continual improvement opportunities. Knowledge and skills Experience as a Data Engineer or Analyst Databricks/Apache Spark SQL/Python BitBucket/GitHub. Advantageous dbt AWS Azure Devops Terraform Atlassian (Jira, Confluence) About Us What's in it for you... Healthcare plan, life assurance More ❯

stakeholders in a fast-paced environment Experience in the design and deployment of production data pipelines from ingestion to consumption within a big data architecture, using Java, Python, Scala, Spark, SQL. Experience performing tasks such as writing scripts, extracting data using APIs, writing SQL queries etc. Experience in processing large amounts of structured and unstructured data, including integrating data More ❯

Java, TypeScript, Python, and Go Web libraries and frameworks such as React and Angular Designing, building, and maintaining CI/CD pipelines Big data technologies, such as NiFi, Hadoop, Spark Cloud and containerization technologies such as AWS, OpenShift, Kubernetes, Docker DevOps methodologies, such as infrastructure as code and GitOps Database technologies, e.g. relational databases, Elasticsearch, Mongo Why join Gemba More ❯

Event streaming & messaging (Kafka, Kinesis, NATS, SQS, Pub/Sub) * Observability stacks (OpenTelemetry, Prometheus, Grafana) * IaC (Terraform), security-by-design, OAuth/OIDC, secrets management * Batch & streaming data processing (Spark/Flink/Beam) or columnar analytics (Parquet/Arrow) Career Paths (we're hiring multiple profiles): * Go Backend (API-first): Own product APIs, performance, reliability. * Go Platform (ML More ❯

a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data tools (Spark, etc.). Strong written and verbal communication skills, especially in cross-functional contexts. Bonus Experience (Nice to Have) Exposure to large language models (LLMs) or foundational model adaptation. Previous More ❯

domains. Proficiency in SQL for data extraction, transformation, and pipeline development. Experience with dashboarding and visualization tools (Tableau, Qlik, or similar). Familiarity with big data tools (Snowflake, Databricks, Spark) and ETL processes. Useful experience; Python or R for advanced analytics, automation, or experimentation support. Knowledge of statistical methods and experimentation (A/B testing) preferred. Machine learning and More ❯

training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people More ❯

training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people More ❯

training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people More ❯

training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people More ❯

training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people More ❯

training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people More ❯

days a week – based business need. To Be Considered: Demonstrable expertise and experience working on large-scale Data Engineering projects Strong experience in Python/PySpark, Databricks & Apache Spark Hands on experience with both batch & streaming pipelines Strong experience in AWS and associated tooling (Eg, S3, Glue, Redshift, Lambda, Terraform etc) Experience designing Data Engineering platforms from scratch More ❯