501 to 525 of 869 Permanent Apache Airflow Jobs

including web scraping, parsing, proxy management, and structured feed ingestion. Pipeline Architect: Hands-on experience with batch-style data workflows using tools like dbt, Airflow, or similar equivalents. Cloud Native: Deep expertise in AWS infrastructure (RDS, ECS, S3, Lambda, OpenSearch). Observability Minded: Familiar with modern stacks for performance ...

including web scraping, parsing, proxy management, and structured feed ingestion. Pipeline Architect: Hands-on experience with batch-style data workflows using tools like dbt, Airflow, or similar equivalents. Cloud Native: Deep expertise in AWS infrastructure (RDS, ECS, S3, Lambda, OpenSearch). Observability Minded: Familiar with modern stacks for performance ...

algorithmic problem-solving. Data Platform Experience: Familiarity operating data platforms or data-intensive workloads, including distributed processing and streaming frameworks such as Spark, Airflow, Kafka, or Flink. Kubernetes & Containerization: Deep expertise in Kubernetes cluster design, day-to-day operations, and production troubleshooting across containerized service environments. CI/ ...

algorithmic problem-solving. Data Platform Experience: Familiarity operating data platforms or data-intensive workloads, including distributed processing and streaming frameworks such as Spark, Airflow, Kafka, or Flink. Kubernetes & Containerization: Deep expertise in Kubernetes cluster design, day-to-day operations, and production troubleshooting across containerized service environments. CI/ ...

algorithmic problem-solving. Data Platform Experience: Familiarity operating data platforms or data-intensive workloads, including distributed processing and streaming frameworks such as Spark, Airflow, Kafka, or Flink. Kubernetes & Containerization: Deep expertise in Kubernetes cluster design, day-to-day operations, and production troubleshooting across containerized service environments. CI/ ...

algorithmic problem-solving. Data Platform Experience: Familiarity operating data platforms or data-intensive workloads, including distributed processing and streaming frameworks such as Spark, Airflow, Kafka, or Flink. Kubernetes & Containerization: Deep expertise in Kubernetes cluster design, day-to-day operations, and production troubleshooting across containerized service environments. CI/ ...

algorithmic problem-solving. Data Platform Experience: Familiarity operating data platforms or data-intensive workloads, including distributed processing and streaming frameworks such as Spark, Airflow, Kafka, or Flink. Kubernetes & Containerization: Deep expertise in Kubernetes cluster design, day-to-day operations, and production troubleshooting across containerized service environments. CI/ ...

OAuth) and secure-by-default practices. Strong Python development skills with production experience. Experience with Kubernetes in production. Familiarity with workflow orchestration tools (Temporal, Airflow, Kubeflow, or similar). Cloud platform experience (AWS preferred, Azure & GCP a plus). Familiarity with data processing frameworks (Spark, Athena, Ray, or similar ...

algorithmic problem-solving. Data Platform Experience: Familiarity operating data platforms or data-intensive workloads, including distributed processing and streaming frameworks such as Spark, Airflow, Kafka, or Flink. Kubernetes & Containerization: Deep expertise in Kubernetes cluster design, day-to-day operations, and production troubleshooting across containerized service environments. CI/ ...

algorithmic problem-solving. Data Platform Experience: Familiarity operating data platforms or data-intensive workloads, including distributed processing and streaming frameworks such as Spark, Airflow, Kafka, or Flink. Kubernetes & Containerization: Deep expertise in Kubernetes cluster design, day-to-day operations, and production troubleshooting across containerized service environments. CI/ ...

schemas to support business requirements Develop and maintain data ingestion and processing systems using various tools and technologies, such as SQL, NoSQL, ETL, Luigi, Airflow, Argo, etc. Implement data storage solutions using different types of databases, such as relational, non-relational, or cloud-based. Working collaboratively with the client …/Azure SQL, PostgreSQL) You have framework experience within either Flask, Tornado or Django, Docker Experience working with ETL pipelines is desirable e.g. Luigi, Airflow or Argo Experience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc. Data acquisition and development of data sets and improving ...

transaction data.• Develop reusable transformation models and curated datasets in Snowflake and dbt for analytics and operational use cases.• Orchestrate complex dependencies with Airflow, Dagster, or a comparable workflow platform.• Design data models and interfaces that are clear, scalable, and easy for downstream teams to use.Raise reliability and data … modern cloud data platform, plus practical knowledge of dimensional and analytical data modeling.• Production experience with dbt or a comparable transformation framework and with Airflow, Dagster, Prefect, or similar orchestration tooling.• Experience with AWS data services and cloud storage; equivalent experience on another major cloud platform is welcome. ...

workbenches, document intelligence platforms, prompt playgrounds, feedback loops, approval workflows, and human-in-the-loop systems. Implement data engineering pipelines using Spark, PySpark, Databricks, Airflow, Kafka, Snowflake, BigQuery, Redshift, SQL, NoSQL, and cloud-native data services. Build ingestion pipelines for structured, semi-structured, and unstructured data including PDFs, Word … with Docker, Kubernetes, Helm, Terraform, CI/CD pipelines , and cloud-native deployments. Strong data engineering skills using SQL, Python, Spark/PySpark, Databricks, Airflow, Kafka , and cloud data platforms. Experience implementing observability, monitoring, logging, tracing, and evaluation for AI/ML/LLM applications. Strong understanding of LLMOps ...

workbenches, document intelligence platforms, prompt playgrounds, feedback loops, approval workflows, and human-in-the-loop systems. Implement data engineering pipelines using Spark, PySpark, Databricks, Airflow, Kafka, Snowflake, BigQuery, Redshift, SQL, NoSQL, and cloud-native data services. Build ingestion pipelines for structured, semi-structured, and unstructured data including PDFs, Word … with Docker, Kubernetes, Helm, Terraform, CI/CD pipelines , and cloud-native deployments. Strong data engineering skills using SQL, Python, Spark/PySpark, Databricks, Airflow, Kafka , and cloud data platforms. Experience implementing observability, monitoring, logging, tracing, and evaluation for AI/ML/LLM applications. Strong understanding of LLMOps ...

workbenches, document intelligence platforms, prompt playgrounds, feedback loops, approval workflows, and human-in-the-loop systems. Implement data engineering pipelines using Spark, PySpark, Databricks, Airflow, Kafka, Snowflake, BigQuery, Redshift, SQL, NoSQL, and cloud-native data services. Build ingestion pipelines for structured, semi-structured, and unstructured data including PDFs, Word … with Docker, Kubernetes, Helm, Terraform, CI/CD pipelines , and cloud-native deployments. Strong data engineering skills using SQL, Python, Spark/PySpark, Databricks, Airflow, Kafka , and cloud data platforms. Experience implementing observability, monitoring, logging, tracing, and evaluation for AI/ML/LLM applications. Strong understanding of LLMOps ...

workbenches, document intelligence platforms, prompt playgrounds, feedback loops, approval workflows, and human-in-the-loop systems. Implement data engineering pipelines using Spark, PySpark, Databricks, Airflow, Kafka, Snowflake, BigQuery, Redshift, SQL, NoSQL, and cloud-native data services. Build ingestion pipelines for structured, semi-structured, and unstructured data including PDFs, Word … with Docker, Kubernetes, Helm, Terraform, CI/CD pipelines , and cloud-native deployments. Strong data engineering skills using SQL, Python, Spark/PySpark, Databricks, Airflow, Kafka , and cloud data platforms. Experience implementing observability, monitoring, logging, tracing, and evaluation for AI/ML/LLM applications. Strong understanding of LLMOps ...

workbenches, document intelligence platforms, prompt playgrounds, feedback loops, approval workflows, and human-in-the-loop systems. Implement data engineering pipelines using Spark, PySpark, Databricks, Airflow, Kafka, Snowflake, BigQuery, Redshift, SQL, NoSQL, and cloud-native data services. Build ingestion pipelines for structured, semi-structured, and unstructured data including PDFs, Word … with Docker, Kubernetes, Helm, Terraform, CI/CD pipelines , and cloud-native deployments. Strong data engineering skills using SQL, Python, Spark/PySpark, Databricks, Airflow, Kafka , and cloud data platforms. Experience implementing observability, monitoring, logging, tracing, and evaluation for AI/ML/LLM applications. Strong understanding of LLMOps ...

workbenches, document intelligence platforms, prompt playgrounds, feedback loops, approval workflows, and human-in-the-loop systems. Implement data engineering pipelines using Spark, PySpark, Databricks, Airflow, Kafka, Snowflake, BigQuery, Redshift, SQL, NoSQL, and cloud-native data services. Build ingestion pipelines for structured, semi-structured, and unstructured data including PDFs, Word … with Docker, Kubernetes, Helm, Terraform, CI/CD pipelines , and cloud-native deployments. Strong data engineering skills using SQL, Python, Spark/PySpark, Databricks, Airflow, Kafka , and cloud data platforms. Experience implementing observability, monitoring, logging, tracing, and evaluation for AI/ML/LLM applications. Strong understanding of LLMOps ...

workbenches, document intelligence platforms, prompt playgrounds, feedback loops, approval workflows, and human-in-the-loop systems. Implement data engineering pipelines using Spark, PySpark, Databricks, Airflow, Kafka, Snowflake, BigQuery, Redshift, SQL, NoSQL, and cloud-native data services. Build ingestion pipelines for structured, semi-structured, and unstructured data including PDFs, Word … with Docker, Kubernetes, Helm, Terraform, CI/CD pipelines , and cloud-native deployments. Strong data engineering skills using SQL, Python, Spark/PySpark, Databricks, Airflow, Kafka , and cloud data platforms. Experience implementing observability, monitoring, logging, tracing, and evaluation for AI/ML/LLM applications. Strong understanding of LLMOps ...

workbenches, document intelligence platforms, prompt playgrounds, feedback loops, approval workflows, and human-in-the-loop systems. Implement data engineering pipelines using Spark, PySpark, Databricks, Airflow, Kafka, Snowflake, BigQuery, Redshift, SQL, NoSQL, and cloud-native data services. Build ingestion pipelines for structured, semi-structured, and unstructured data including PDFs, Word … with Docker, Kubernetes, Helm, Terraform, CI/CD pipelines , and cloud-native deployments. Strong data engineering skills using SQL, Python, Spark/PySpark, Databricks, Airflow, Kafka , and cloud data platforms. Experience implementing observability, monitoring, logging, tracing, and evaluation for AI/ML/LLM applications. Strong understanding of LLMOps ...

workbenches, document intelligence platforms, prompt playgrounds, feedback loops, approval workflows, and human-in-the-loop systems. Implement data engineering pipelines using Spark, PySpark, Databricks, Airflow, Kafka, Snowflake, BigQuery, Redshift, SQL, NoSQL, and cloud-native data services. Build ingestion pipelines for structured, semi-structured, and unstructured data including PDFs, Word … with Docker, Kubernetes, Helm, Terraform, CI/CD pipelines , and cloud-native deployments. Strong data engineering skills using SQL, Python, Spark/PySpark, Databricks, Airflow, Kafka , and cloud data platforms. Experience implementing observability, monitoring, logging, tracing, and evaluation for AI/ML/LLM applications. Strong understanding of LLMOps ...

workbenches, document intelligence platforms, prompt playgrounds, feedback loops, approval workflows, and human-in-the-loop systems. Implement data engineering pipelines using Spark, PySpark, Databricks, Airflow, Kafka, Snowflake, BigQuery, Redshift, SQL, NoSQL, and cloud-native data services. Build ingestion pipelines for structured, semi-structured, and unstructured data including PDFs, Word … with Docker, Kubernetes, Helm, Terraform, CI/CD pipelines , and cloud-native deployments. Strong data engineering skills using SQL, Python, Spark/PySpark, Databricks, Airflow, Kafka , and cloud data platforms. Experience implementing observability, monitoring, logging, tracing, and evaluation for AI/ML/LLM applications. Strong understanding of LLMOps ...

workbenches, document intelligence platforms, prompt playgrounds, feedback loops, approval workflows, and human-in-the-loop systems. Implement data engineering pipelines using Spark, PySpark, Databricks, Airflow, Kafka, Snowflake, BigQuery, Redshift, SQL, NoSQL, and cloud-native data services. Build ingestion pipelines for structured, semi-structured, and unstructured data including PDFs, Word … with Docker, Kubernetes, Helm, Terraform, CI/CD pipelines , and cloud-native deployments. Strong data engineering skills using SQL, Python, Spark/PySpark, Databricks, Airflow, Kafka , and cloud data platforms. Experience implementing observability, monitoring, logging, tracing, and evaluation for AI/ML/LLM applications. Strong understanding of LLMOps ...

workbenches, document intelligence platforms, prompt playgrounds, feedback loops, approval workflows, and human-in-the-loop systems. Implement data engineering pipelines using Spark, PySpark, Databricks, Airflow, Kafka, Snowflake, BigQuery, Redshift, SQL, NoSQL, and cloud-native data services. Build ingestion pipelines for structured, semi-structured, and unstructured data including PDFs, Word … with Docker, Kubernetes, Helm, Terraform, CI/CD pipelines , and cloud-native deployments. Strong data engineering skills using SQL, Python, Spark/PySpark, Databricks, Airflow, Kafka , and cloud data platforms. Experience implementing observability, monitoring, logging, tracing, and evaluation for AI/ML/LLM applications. Strong understanding of LLMOps ...

workbenches, document intelligence platforms, prompt playgrounds, feedback loops, approval workflows, and human-in-the-loop systems. Implement data engineering pipelines using Spark, PySpark, Databricks, Airflow, Kafka, Snowflake, BigQuery, Redshift, SQL, NoSQL, and cloud-native data services. Build ingestion pipelines for structured, semi-structured, and unstructured data including PDFs, Word … with Docker, Kubernetes, Helm, Terraform, CI/CD pipelines , and cloud-native deployments. Strong data engineering skills using SQL, Python, Spark/PySpark, Databricks, Airflow, Kafka , and cloud data platforms. Experience implementing observability, monitoring, logging, tracing, and evaluation for AI/ML/LLM applications. Strong understanding of LLMOps ...