201 to 225 of 377 Apache Airflow Jobs

Strong hands-on experience with SQL, ETL processes, and data warehousing concepts. Knowledge of Snow pipe, Tasks, Streams, and Time Travel features. Experience with Python or ETL tools (e.g., Airflow, Talend, Informatica) is a plus. Fluent in Mandarin Chinese (spoken and written) and proficient in English. 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 ❯

NoSQL Specialization in designing and implementing large-scale data pipelines, ETL processes, and distributed systems Should be able to work independenty with minimal help/guidance Good Understanding of Airflow,Data Fusion and Data Flow Strong Background and experience in Data Ingestions,Transformation,Modeling and Performance tuning. One migration Experience from Cornerstone to GCP will be added advantage Suppport More ❯

NoSQL Specialization in designing and implementing large-scale data pipelines, ETL processes, and distributed systems Should be able to work independenty with minimal help/guidance Good Understanding of Airflow,Data Fusion and Data Flow Strong Background and experience in Data Ingestions,Transformation,Modeling and Performance tuning. One migration Experience from Cornerstone to GCP will be added advantage Suppport More ❯

have strong, proven experience in a contracting capacity with: Python SQL Azure Fabric Highly advantageous if you have: dbt (Data Build Tool) Data Warehousing expertise Modern orchestration tools (e.g., Airflow, Dagster, Prefect) Public sector experience React Clearance: You must hold active SC Clearance to be considered. More ❯

have strong, proven experience in a contracting capacity with: Python SQL Azure Fabric Highly advantageous if you have: dbt (Data Build Tool) Data Warehousing expertise Modern orchestration tools (e.g., Airflow, Dagster, Prefect) Public sector experience React Clearance: You must hold active SC Clearance to be considered. More ❯

challenges. What you'll need: Solid hands-on experience with Python and SQL Strong knowledge of data pipelines, cloud infrastructure (AWS & Azure), and integration tools Familiarity with tools like Airflow and version control, GIT. Confident working with structured and unstructured datasets Comfortable contributing to both technical delivery and collaborative problem-solving Salary and Benefits: This role is paying a More ❯

challenges. What you'll need: Solid hands-on experience with Python and SQL Strong knowledge of data pipelines, cloud infrastructure (AWS & Azure), and integration tools Familiarity with tools like Airflow and version control, GIT. Confident working with structured and unstructured datasets Comfortable contributing to both technical delivery and collaborative problem-solving Salary and Benefits: This role is paying a More ❯

. Advanced SQL and dimensional data modelling skills (fact/dimension design, hierarchies, SCDs). Proven experience building ETL/ELT pipelines using tools such as SSIS , dbt , or Airflow . Solid understanding of database administration , tuning, and performance optimisation across MSSQL and PostgreSQL . Key Responsibilities: Design and maintain data models that meet business requirements, ensuring scalability, consistency More ❯

. Advanced SQL and dimensional data modelling skills (fact/dimension design, hierarchies, SCDs). Proven experience building ETL/ELT pipelines using tools such as SSIS , dbt , or Airflow . Solid understanding of database administration , tuning, and performance optimisation across MSSQL and PostgreSQL . Key Responsibilities: Design and maintain data models that meet business requirements, ensuring scalability, consistency More ❯

warehousing and transformation. Strong SQL skills and understanding of modern data architecture principles. Hands-on experience with Tableau for enterprise-grade dashboard development. Familiarity with orchestration tools (e.g., Prefect, Airflow), data quality frameworks, and metadata tools. Proficiency in Git, CI/CD, and scripting with Python. Excellent communication skills and ability to work collaboratively across technical and business teams. More ❯

and PySpark Exposure to generative AI platforms or a passion for building AI-powered solutions Ability to lead client delivery in dynamic, fast-paced environments Familiarity with tools like Airflow, Databricks or DBT is a plus What's on offer: Salary up to £75,000 Bonus and equity options Hybrid working: 3 days in a vibrant central London office More ❯

warehousing and transformation. Strong SQL skills and understanding of modern data architecture principles. Hands-on experience with Tableau for enterprise-grade dashboard development. Familiarity with orchestration tools (e.g., Prefect, Airflow), data quality frameworks, and metadata tools. Proficiency in Git, CI/CD, and scripting with Python. Excellent communication skills and ability to work collaboratively across technical and business teams. More ❯

and PySpark Exposure to generative AI platforms or a passion for building AI-powered solutions Ability to lead client delivery in dynamic, fast-paced environments Familiarity with tools like Airflow, Databricks or DBT is a plus What's on offer: Salary up to £75,000 Bonus and equity options Hybrid working: 3 days in a vibrant central London office More ❯

machine learning. Proven experience delivering production-grade AI/ML applications, including LLMs and anomaly detection models. Familiarity with cloud infrastructure (AWS preferred), container orchestration (Kubernetes), and workflow tools (Airflow, Argo). Experience with observability tools (e.g., Grafana, CloudWatch) and RESTful API development. More ❯

architecture, build data pipelines, and integrate AI/LLM components into production systems. Role Breakdown: 50% Backend Engineering: FastAPI, Flask, Node.js, CI/CD 30% Data Engineering: ETL, DBT, Airflow 20% AI/LLM Integration: LangChain, RAG pipelines, orchestration Key Responsibilities: Design and build backend services to support AI agent deployment Develop scalable data pipelines and integration layers Implement More ❯

architecture, build data pipelines, and integrate AI/LLM components into production systems. Role Breakdown: 50% Backend Engineering: FastAPI, Flask, Node.js, CI/CD 30% Data Engineering: ETL, DBT, Airflow 20% AI/LLM Integration: LangChain, RAG pipelines, orchestration Key Responsibilities: Design and build backend services to support AI agent deployment Develop scalable data pipelines and integration layers Implement More ❯

Data Engineer (Databricks) Deep hands-on experience with Databricks, Delta Live Tables (DLT), data modelling, data ingestion & integration Strong proficiency across Data Factory, SQL DB, Synapse, Stream Analytics, Glue, Airflow, Kinesis, Redshift, GITHUB/DevOps tools, testing frameworks (SonarQube/PyTest) Proven experience leading data engineering teams while remaining actively hands-on involved in delivery Background within energy, utilities More ❯

Data Engineer (Databricks) Deep hands-on experience with Databricks, Delta Live Tables (DLT), data modelling, data ingestion & integration Strong proficiency across Data Factory, SQL DB, Synapse, Stream Analytics, Glue, Airflow, Kinesis, Redshift, GITHUB/DevOps tools, testing frameworks (SonarQube/PyTest) Proven experience leading data engineering teams while remaining actively hands-on involved in delivery Background within energy, utilities More ❯

TO HAVE: Experience integrating AI models into production systems using GCP, AWS, or Azure. Familiarity with vector databases, embedding models, or retrieval-augmented generation (RAG). Knowledge of Docker, Airflow, or MLOps pipelines. Strong understanding of AI ethics, data privacy, and responsible model deployment. TO BE CONSIDERED... Please either apply online or email me directly at .By applying for More ❯

in Data Engineering , ideally in cloud-native or AI-oriented environments. Strong Python skills for data pipeline and service development. Proficiency with AWS (Lambda, S3, Glue) and orchestration tools (Airflow, Dagster, etc.). Familiarity with relational and vector databases (PostgreSQL, Pinecone, MySQL). Understanding of API development and event-driven architectures. A mindset that’s curious, collaborative, and driven More ❯

in Data Engineering , ideally in cloud-native or AI-oriented environments. Strong Python skills for data pipeline and service development. Proficiency with AWS (Lambda, S3, Glue) and orchestration tools (Airflow, Dagster, etc.). Familiarity with relational and vector databases (PostgreSQL, Pinecone, MySQL). Understanding of API development and event-driven architectures. A mindset that’s curious, collaborative, and driven More ❯

analysts, and client stakeholders to deliver reliable, automated, and high-performing data solutions end to end. What We're Looking For • Strong experience with Python, Databricks and tools like Airflow • Confident working across Cloud Platforms (AWS, Azure, GCP) • Great communication skills and the ability to work with both technical and non-technical teams • Comfortable in a consultancy setting, balancing More ❯

analysts, and client stakeholders to deliver reliable, automated, and high-performing data solutions end to end. What We’re Looking For Strong experience with Python, Databricks and tools like Airflow Confident working across Cloud Platforms (AWS, Azure, GCP) Great communication skills and the ability to work with both technical and non-technical teams Comfortable in a consultancy setting, balancing More ❯

tools. Knowledge of event streaming, API integration, and MLOps . Experience in regulated, high-volume industries (gaming, finance, or e-commerce). Proficiency with integration/orchestration tools like Airflow and dbt . Why this role is a game-changer for you You'll be making a huge impact on our products, player experience, and internal processes . This More ❯