101 to 125 of 185 Permanent Apache Airflow Jobs

Data Engineer - FinTech - Newcastle (Tech stack: Data Engineer, SQL, Python, AWS, Git, Airflow, Data Pipelines, Data Platforms, Programmer, Developer, Architect, Data Engineer) Our client is a trailblazer in the FinTech space, known for delivering innovative technology solutions to global financial markets. They are expanding their engineering capability in Newcastle and are looking for a talented Data Engineer to join More ❯

pipelines in Python that run smoothly and efficiently. You understand how to analyze data, spot trends, and communicate your findings clearly. Bonus points if you have worked with DBT, Airflow, Terraform, or have an interest in machine learning and advanced analytics. Above all, you want to grow your technical skills while building things that get used right away. Wat 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 ❯

drug discovery, combining quantum-inspired physics with generative models Real-World Impact : Every feature shipped helps scientists prioritize molecules and design better candidates, faster Modern Stack & Challenges : Python, FastAPI, Airflow, Snowflake, Kubernetes, ML workflows, scientific infra, data engineering at scale High Ownership, High Impact : Engineers contribute to architecture, tooling, and scientific decision-making Interdisciplinary Team : Collaborate with chemists, physicists More ❯

Python and SQL fundamentals The ability to get to grips with new technologies quickly What's Nice to Have Experience in dashboarding tools, Typescript and API development Familiarity with Airflow, DBT, Databricks Experience working with Enterprise Resource Planning (e.g. Oracle, SAP) and CRM systems Benefits Become part of a category-defining startup which transforms transforming how industrial companies operate More ❯

Scala, or in a language such as Java or Python that supports a quick transition to Scala Working with big data technologies, ideally Spark, but experience with tools like Airflow or Elasticsearch is also valuable Manipulating and transforming data - cleansing, parsing, standardising - to improve data quality and integrity Why join Quantexa? Our perks and quirks. What makes you Q More ❯

building and scaling Extract, Load, Transform (ELT) pipelines. Experience overseeing or managing projects involving data pipeline orchestration, data quality management, and performance optimization. Knowledge of common ELT tools like Apache Airflow, Informatica PowerCenter, or cloud-native data integration services is a plus • Data Science/AI & Data Standards: Understanding of how data standards impact data science and AI More ❯

MLflow for ML lifecycle management and model versioning Hands-on experience with Databricks Model Serving for production ML deployments Proficiency with GenAI frameworks/tools and technologies such as Apache Airflow, Spark, Flink, Kafka/Kinesis, Snowflake, and Databricks. Demonstrable experience in parameter-efficient fine-tuning, model quantization, and quantization-aware fine-tuning of LLM models Hands-on More ❯

time Preferred Skills: Experience with frameworks: TensorFlow, PyTorch, Keras Knowledge of LLMs, GANs, or Reinforcement Learning Familiarity with MLOps tools like MLflow, SageMaker, Vertex AI Understanding of ETL pipelines, Airflow, Kafka, or Spark More ❯

communication skills. Bonus Points For: Experience leading projects in SCIF environments. Expertise in Cyber Analytics, PCAP, or network monitoring. Familiarity with Spark, Dask, Snowpark, Kafka, or task schedulers like Airflow and Celery. More ❯

or PySpark Exposure to generative AI platforms or interest in building AI-powered workflows Ability to work closely with clients and lead delivery in fast-paced environments Exposure to Airflow, Databricks or DBT would be beneficial Some of the package details include: Salary up to £75,000 per year Bonus and share options Vibrant central London office, working closely More ❯

or PySpark Exposure to generative AI platforms or interest in building AI-powered workflows Ability to work closely with clients and lead delivery in fast-paced environments Exposure to Airflow, Databricks or DBT would be beneficial Some of the package details include: Salary up to £75,000 per year Bonus and share options Vibrant central London office, working closely More ❯

including PCAP, CVEs, and network monitoring. Experience integrating with technologies such as Spark, Dask, Snowpark, or Kafka. Background in web application stacks (e.g., Flask, Django) or task schedulers (e.g., Airflow, Celery, Prefect). Compensation & Benefits: Competitive salary, equity, and performance-based bonus. Full benefits package including medical, dental, and vision. Unlimited paid time off. If you want to know More ❯

passion for new technologies Experience in startups or top-tier consultancies is a plus Nice to Have (not essential): Familiarity with dashboarding tools, Typescript, and API development Exposure to Airflow, DBT, Databricks Experience with ERP (e.g. SAP, Oracle) and CRM systems What's On Offer: Salary: £50,000-£75,000 + share options Hybrid working: 2-3 days per More ❯

passion for new technologies Experience in startups or top-tier consultancies is a plus Nice to Have (not essential): Familiarity with dashboarding tools, Typescript, and API development Exposure to Airflow, DBT, Databricks Experience with ERP (e.g. SAP, Oracle) and CRM systems What's On Offer: Salary: £50,000-£75,000 + share options Hybrid working: 2-3 days per More ❯

material sciences, or other research-heavy fields. Leadership & Mentorship: Experience guiding peers in backend best practices, performance optimization, and system design. Orchestration Systems: Experience with orchestration tools (Flyte, Kubeflow, Airflow, Prefect, Dagster). Domain Background: Exposure to analytics for life sciences, material sciences, or related fields. We're All In Lila Sciences is committed to equal employment opportunity regardless More ❯

and AI , or other deep learning-related independent project work with evidence of completion. Experience with data ingestion or processing tools and frameworks, such as Docling, Spark, Pandas, Feast, Airflow, NumPy . Experience with retrieval augmented generation approaches, including vector databases and dense retrieval methods. Knowledgeable in various synthetic data generation approaches, such as GANs, VAEs, or rule-based More ❯

Bachelor’s degree in Information Technology or equivalent experience · Demonstrated experience with Cloud technologies like AWS or GCP. · Demonstrated expertise in developing ETL pipelines and Data Orchestration tools like Apache Airflow. · Strong understanding of Relational Database concepts (i.e. normalization, constraints, etc) · Good understanding of Web Technologies including APIs and SSO. · Proficient at troubleshooting technical issues (query performance, data integration More ❯

Terraform (Cloud/Open Source) for cloud infrastructure automation. Proficiency with Databricks: clusters, jobs, notebooks, DBFS, and workspace management. Hands-on experience with MLOps tools (e.g., MLflow, TFX, Kubeflow, Airflow, or SageMaker Pipelines Experience deploying and scaling Large Language Models (LLMs) in production environments. Proficiency in CI/CD tooling (GitHub Actions, Azure DevOps, GitLab CI, etc. Scripting and More ❯

Master ELT - Master Data Modeling - Master Data Integration & Ingestion - Skill Data Manipulation and Processing - Skill GITHUB, Action, Azure DevOps - Skill Data factory, Databricks, SQL DB, Synapse, Stream Analytics, Glue, Airflow, Kinesis, Redshift, SonarQube, PyTest - Skill More ❯

network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience More ❯

network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience More ❯

network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience More ❯

network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience More ❯

network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience More ❯