1 to 25 of 36 Remote Apache Airflow Jobs in the UK excluding London

Data Engineer (AI-Driven SaaS plaform) (Python, Snowflake, Data Modelling, ETL/ELT, Apache Airflow, Kafka, AWS) Large-scale data environment Up to £70,000 plus benefits FULLY REMOTE UK Are you a Data Engineering enthusiast who thrives from designing and implementing robust ETL processes, highly scalable data structures and data pipelines within a truly enterprise-scale data … platform integrates Python and Snowflake and you'll need a deep understanding of SQL and NoSQL databases (MongoDB or similar!) You'll also have exposure with streaming platforms like Apache Kafka and be able to develop and maintain ELT and essentially bring a solid understanding of data warehousing concepts and best practice. Essentially, a strong Data Engineer who is … a Snowflake enthusiast who can write solid SQL queries, within Snowflake! You will understanding Apache Kafka to a high standard and have solid knowledge of Apache Airflow - from a Cloud perspective, good AWS exposure. Naturally you will have good understanding on AWS. I'd love you to be an advocate of Agile too - these guys are massive More ❯

data pipelines within enterprise-grade on-prem systems. Key Responsibilities: Design, develop, and maintain data pipelines using Hadoop technologies in an on-premises infrastructure. Build and optimise workflows using Apache Airflow and Spark Streaming for real-time data processing. Develop robust data engineering solutions using Python for automation and transformation. Collaborate with infrastructure and analytics teams to support … platform. Ensure compliance with enterprise security and data governance standards. Required Skills & Experience: Minimum 5 years of experience in Hadoop and data engineering. Strong hands-on experience with Python, Apache Airflow, and Spark Streaming. Deep understanding of Hadoop components (HDFS, Hive, HBase, YARN) in on-prem environments. Exposure to data analytics, preferably involving infrastructure or operational data. Experience More ❯

of real-time and analytical data pipelines, metadata, and cataloguing (e.g., Atlan) Strong communication, stakeholder management, and documentation skills Preferred (but not essential): AWS or Snowflake certifications Knowledge of Apache Airflow, DBT, GitHub Actions Experience with Iceberg tables and data product thinking Why Apply? Work on high-impact, high-scale client projects Join a technically elite team with More ❯

services (e.g., S3, Glue, Lambda, Redshift, Athena, EMR). Experience designing and building data lakes and modern data platforms. Proficiency with Python, SQL, and data pipeline orchestration tools (e.g., Airflow, dbt). Strong understanding of data modelling, ETL/ELT processes, and distributed systems. Knowledge of data security, governance, and compliance best practices. Excellent leadership, communication, and stakeholder engagement More ❯

in a commercial setting. Solid understanding of distributed systems (e.g. Hadoop, AWS, Kafka). Experience with SQL/NoSQL databases (e.g. PostgreSQL, Cassandra). Familiarity with orchestration tools (e.g. Airflow, Luigi) and cloud platforms (e.g. AWS, GCP). Passion for solving complex problems and mentoring others. Package: Salary from £(phone number removed) depending on experience Remote-first with flexible More ❯

e.g., Git), and strong problem-solving skills are vital. The ability to communicate technical concepts clearly to non-technical stakeholders is also important. Experience with orchestration tools such as Airflow, knowledge of Python or other scripting languages, and familiarity with data governance and security best practices are desirable. Exposure to agile development environments, performance tuning of data queries, and More ❯

fine-tuning techniques including LoRA, QLoRA, and parameter efficient methods - Multi-modal AI systems combining text, image, and structured data - Reinforcement Learning from Human Feedback (RLHF) for model alignment - Apache Airflow/Dagster for ML workflow orchestration and ETL pipeline management - Model versioning and experiment tracking (MLflow, Weights & Biases) - Real-time model serving and edge deployment strategies - A More ❯

fine-tuning techniques including LoRA, QLoRA, and parameter efficient methods - Multi-modal AI systems combining text, image, and structured data - Reinforcement Learning from Human Feedback (RLHF) for model alignment - Apache Airflow/Dagster for ML workflow orchestration and ETL pipeline management - Model versioning and experiment tracking (MLflow, Weights & Biases) - Real-time model serving and edge deployment strategies - A More ❯

fine-tuning techniques including LoRA, QLoRA, and parameter efficient methods - Multi-modal AI systems combining text, image, and structured data - Reinforcement Learning from Human Feedback (RLHF) for model alignment - Apache Airflow/Dagster for ML workflow orchestration and ETL pipeline management - Model versioning and experiment tracking (MLflow, Weights & Biases) - Real-time model serving and edge deployment strategies - A More ❯

Transformers , PyTorch , YOLO , OpenCV , and Pillow Designing and deploying AI services via FastAPI , AWS Lambda , EKS/ECS , and S3 Creating scalable data pipelines with Pandas , NumPy , SQLAlchemy , and Airflow Supporting real-time model inference, edge deployments, and API integrations Working closely with a technical lead in a service-based and serverless architecture Essential Python Engineer skills and experience More ❯

ideally within consumer tech, logistics, or e-commerce. Strong proficiency in Python, SQL, and machine learning frameworks. Experience with cloud platforms (Azure, AWS, GCP) and tools like Databricks, DBT, Airflow, or Terraform. Familiarity with AI/ML applications and modern analytics tooling. Excellent communication skills and ability to work independently in a fast-paced environment. Why Join? Be part More ❯

teams Strong technical background (5+ years) in building scalable data platforms Excellent communication and stakeholder management skills Hands-on experience with modern data tools and technologies — Python, SQL, Snowflake, Airflow, dbt, Spark, AWS, Terraform A collaborative mindset and a passion for mentoring and developing others Comfortable balancing technical decisions with business needs Nice to have: experience with Data Mesh More ❯

As a Senior Data Engineer you will take ownership of the data platform, optimising it for scalability to ensure successful client onboarding. You'll use modern tools (such as Airflow, Prefect, Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication More ❯

e.g., Erwin, Lucidchart). Strong grasp of data governance, metadata management, and compliance frameworks (e.g., GDPR). Hands-on understanding of Python, SQL, and modern data engineering tools (e.g., Airflow, DBT, Atlan). Exceptional consulting and stakeholder management skills. Career experience within leading consultancies or SIs (e.g., IBM, Thoughtworks, EY, Capgemini). What's on Offer More ❯

development efficiency and deployment effectiveness, including Azure DevOps or GitHub Considerable experience designing and building operationally efficient pipelines, utilising core Cloud components, such as Azure Data Factory, Big Query, AirFlow, Google Cloud Composer and Pyspark etc Proven experience in modelling data through a medallion-based architecture, with curated dimensional models in the gold layer built for analytical use Strong More ❯

the role you will have: Creating scalable ETL jobs using Scala and Spark Strong understanding of data structures, algorithms, and distributed systems Experience working with orchestration tools such as Airflow Familiarity with cloud technologies (AWS or GCP) Hands-on experience with Gen AI tools for coding and debugging This is a remote-first role with flexibility to work from More ❯

best practices in testing, data governance, and observability. Lead roadmap planning and explore emerging technologies (e.g. GenAI). Ensure operational stability and support incident resolution. Tech Stack Python , SQL , Airflow , AWS , Fivetran , Snowflake , Looker , Docker (You don't need to tick every box - if you've worked with comparable tools, that's great too.) What We're Looking For More ❯

Bonus skills Experience in any of the following is a plus: Python, Scala, or data processing frameworks Event-driven or distributed system architectures Big data tools (e.g., Hadoop, HDFS, Airflow) Linux and containerisation Why join? This is an exciting opportunity to be at the forefront of large-scale, cloud-first transformation efforts. You'll help shape platforms that power More ❯

Bonus skills Experience in any of the following is a plus: Python, Scala, or data processing frameworks Event-driven or distributed system architectures Big data tools (e.g., Hadoop, HDFS, Airflow) Linux and containerisation Why join? This is an exciting opportunity to be at the forefront of large-scale, cloud-first transformation efforts. You'll help shape platforms that power More ❯

contexts. Bonus Experience (Nice to Have) Exposure to large language models (LLMs) or foundational model adaptation. Previous work in cybersecurity, anomaly detection, or behavioural analytics. Familiarity with orchestration frameworks (Airflow or similar). Experience with scalable ML systems, pipelines, or real-time data processing. Advanced degree or equivalent experience in ML/AI research or applied science. Cloud platform More ❯

datasets into actionable insights for the business. In this role, you will: Develop and maintain a cloud-based data warehouse (BigQuery, GCP) Create and optimise ETL processes (SSIS, Talend, Airflow) Collaborate with BI teams to deliver key performance metrics Ensure data quality, security, and cost-efficient storage What you'll bring: Strong SQL and data modelling skills Data warehouse More ❯

systems. Deploy scalable AI systems using AWS (Lambda, S3, SQS, EKS/ECS), CDK , and modern DevOps practices. Collaborate on infrastructure and data pipelines using SQLAlchemy, Boto3, Pandas, and Airflow . Contribute to real-time AI services , model versioning, and advanced fine-tuning (LoRA, QLoRA, etc.). AI Engineer requirements: Solid Python skills (3.9+) with deep knowledge of async More ❯

Experience in ELT processes and best practices for cloud-based data warehousing. Knowledge of performance tuning techniques for optimising BigQuery queries and costs. Familiarity with cloud services (GCP, Terraform, Airflow, etc.) and their integration with BigQuery. HOW TO APPLY Please register your interest by sending your CV via the apply link on this page. More ❯

focus on practical application and performance trade-offs. Experience with cloud platforms (e.g., AWS, Azure) and containerisation (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, SageMaker, Airflow). Experience working with large-scale datasets and distributed computing frameworks (e.g., Spark). Strong communication skills and ability to work collaboratively in a team environment. MSc or PhD More ❯

focus on practical application and performance trade-offs. Experience with cloud platforms (e.g., AWS, Azure) and containerisation (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, SageMaker, Airflow). Experience working with large-scale datasets and distributed computing frameworks (e.g., Spark). Strong communication skills and ability to work collaboratively in a team environment. MSc or PhD More ❯