51 to 75 of 83 Remote Apache Airflow Jobs

with a passion for new technologies Experience in startups or top-tier consultancies is a plus Nice to Have: 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 ❯

algorithms (supervised, unsupervised, deep learning), including model evaluation, explainability, and selection for business-critical use cases Strong hands-on experience with cloud infrastructure (AWS), containerization (Docker), and orchestration (Jenkins, Airflow) Proven capability in MLOps, including CI/CD pipelines, model monitoring, versioning, and automated retraining Experience deploying and serving models through APIs (e.g., Flask, FastAPI) in both real-time 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 ❯

Engineer for our client within defence/digital transformation. The ideal candidate will be able to solve data engineering problems independently whilst delaing with non-technical SMEs. Requirements: Python, Airflow, Glue & Informatica. SC cleared Details: 6 months Outside IR35 Hybrid/London ASAP start date If this role is of interest, please get in touch. Reference: AMC/DJA 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 ❯

. Ability to collaborate effectively with senior engineers, data scientists, and architects. Proactive, detail-oriented, and eager to contribute within a greenfield project environment. Nice to Have: Experience with Airflow/Astro . Prior work with notebook-based development environments. Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community 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 ❯

/medical devices preferred but not required) Strong Python programming and data engineering skills (Pandas, PySpark, Dask) Proficiency with databases (SQL/NoSQL), ETL processes, and modern data frameworks (Apache Spark, Airflow, Kafka) Solid experience with cloud platforms (AWS, GCP, or Azure) and CI/CD for data pipelines Understanding of data privacy and healthcare compliance (GDPR, HIPAA More ❯

centred around a software product, and have solid Python coding skills, and expertise with cloud infrastructure (preferably AWS). Familiarity with Containers and MLE tools such as MLflow and Airflow is essential, with any knowledge of AI SaaS or GenAI APIs being is a bonus. But what truly matters is your passion for learning and advancing technology. In return More ❯

data pipelines Strong understanding of data modeling, schema design, and lakehouse principles Familiarity with data governance, lineage, and quality frameworks Experience working on enterprise-class applications Preferred: Experience with Apache Spark Hands-on experience with AWS data services (e.g., S3, Glue, Lambda, MSK) Capable in batch or streaming data processing using technologies such as Spark, Kafka, Flink, and DLT … Proficient in CI/CD pipelines, automated testing, code quality enforcement, and environment management for production-grade data systems Expert in orchestration and transformation frameworks such as Airflow, dbt, and Dagster, along with cloud-native platforms like Databricks Financial services or FinTech industry experience Knowledge and Skills: Operates with full autonomy on large-scale, complex data projects. Go to More ❯

analytics, and software development, contributing to innovative products and services that drive real business value. Key Responsibilities Design and implement robust data pipelines using tools such as dbt and Airflow . Collaborate with clients to understand business challenges and deliver tailored data solutions. Transform raw data into structured, actionable datasets for use in AI , predictive modelling , and platform development … the ability to engage stakeholders and translate technical work into business outcomes. Hands-on experience with cloud platforms (preferably AWS or Snowflake) and ETL/ELT orchestration tools (e.g. Airflow, dbt). Desirable Skills Familiarity with tools such as MongoDB , Glue , Athena , and React . Experience in API development and working with modern data infrastructure. Ability to work independently More ❯

analytics, and software development, contributing to innovative products and services that drive real business value. Key Responsibilities Design and implement robust data pipelines using tools such as dbt and Airflow . Collaborate with clients to understand business challenges and deliver tailored data solutions. Transform raw data into structured, actionable datasets for use in AI , predictive modelling , and platform development … the ability to engage stakeholders and translate technical work into business outcomes. Hands-on experience with cloud platforms (preferably AWS or Snowflake) and ETL/ELT orchestration tools (e.g. Airflow, dbt). Desirable Skills Familiarity with tools such as MongoDB , Glue , Athena , and React . Experience in API development and working with modern data infrastructure. Ability to work independently More ❯

development lifecycles, cloud technologies and modern engineering practices. ● Experience with the following technologies: o Cloud Provider: AWS o Languages: Python, PHP, Rust & SQL o Hosting: Kubernetes o Tooling & Analytics: Airflow, RabbitMQ, Apache Spark, PowerBI ● Proven ability to complete projects according to outlined scope, budget, and timeline ● Experience with industry standard tools such as Microsoft products, Jira, confluence, project More ❯

development lifecycles, cloud technologies and modern engineering practices. ● Experience with the following technologies: o Cloud Provider: AWS o Languages: Python, PHP, Rust & SQL o Hosting: Kubernetes o Tooling & Analytics: Airflow, RabbitMQ, Apache Spark, PowerBI ● Proven ability to complete projects according to outlined scope, budget, and timeline ● Experience with industry standard tools such as Microsoft products, Jira, confluence, project More ❯

automation, reliability, and agility. Key Responsibilities Design, build, and optimise data pipelines across a modern data platform. Ingest, clean, and transform data using tools such as dbt, Snowflake, and Airflow . Collaborate with cross-functional teams to deliver data products aligned to business priorities. Develop scalable data models that support BI and analytics platforms including Tableau and Power BI. … and optimise complex queries. Hands-on experience with dbt (including testing and layered modelling). Practical knowledge of Snowflake for loading, transforming, and exporting datasets. Experience building and managing Airflow DAGs for pipeline orchestration. Understanding of BI tool requirements (e.g., Tableau, Power BI) and related performance considerations. Advanced Excel capability, including pivot tables and complex formulas. Familiarity with data More ❯

colleagues. Nice to Have Skills Experience working with GCP (BigQuery) or other modern cloud-native data warehouses (e.g. Snowflake, Redshift). Familiarity with data pipelining and orchestration systems (e.g. Airflow). Understanding of modern analytics architectures and data visualisation tools (we use Preset.io/Apache Superset). Exposure to CI/CD pipelines (GitLab CI preferred). Experience More ❯

colleagues. Nice to Have Skills Experience working with GCP (BigQuery) or other modern cloud-native data warehouses (e.g. Snowflake, Redshift). Familiarity with data pipelining and orchestration systems (e.g. Airflow). Understanding of modern analytics architectures and data visualisation tools (we use Preset.io/Apache Superset). Exposure to CI/CD pipelines (GitLab CI preferred). Experience More ❯

colleagues. Nice to Have Skills Experience working with GCP (BigQuery) or other modern cloud-native data warehouses (e.g. Snowflake, Redshift). Familiarity with data pipelining and orchestration systems (e.g. Airflow). Understanding of modern analytics architectures and data visualisation tools (we use Preset.io/Apache Superset). Exposure to CI/CD pipelines (GitLab CI preferred). Experience More ❯

colleagues. Nice to Have Skills Experience working with GCP (BigQuery) or other modern cloud-native data warehouses (e.g. Snowflake, Redshift). Familiarity with data pipelining and orchestration systems (e.g. Airflow). Understanding of modern analytics architectures and data visualisation tools (we use Preset.io/Apache Superset). Exposure to CI/CD pipelines (GitLab CI preferred). Experience More ❯

colleagues. Nice to Have Skills Experience working with GCP (BigQuery) or other modern cloud-native data warehouses (e.g. Snowflake, Redshift). Familiarity with data pipelining and orchestration systems (e.g. Airflow). Understanding of modern analytics architectures and data visualisation tools (we use Preset.io/Apache Superset). Exposure to CI/CD pipelines (GitLab CI preferred). Experience More ❯