Phoenix - Your AI AssistantOozie/Airflow Workflow & Hadoop Job Orchestration
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5 days
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What you get with this Offer
I will design and implement a Hadoop job orchestration workflow using Apache Oozie or Apache Airflow — scheduling and coordinating your MapReduce, Spark, Hive, Sqoop, and shell action steps into a dependency-managed pipeline with error handling, retry configuration, SLA monitoring, and notification on failure. Hadoop jobs run as cron-scheduled shell scripts are the most common operational problem in Hadoop environments; without dependency management, a failed upstream job silently allows downstream jobs to run on stale data, producing corrupted analytical outputs that are only discovered at the reporting layer.
The workflow covers directed acyclic graph design for your job dependencies, Oozie workflow.xml or Airflow DAG definition, action node configuration for each job type (Spark, Hive, Sqoop, shell), decision nodes for conditional branching, fork/join nodes for parallel execution, error handler and kill node configuration, SLA definition, and email or Slack alerting on failure. A coordinator job for time-triggered execution is included for Oozie.
Designed for data engineering teams running multiple interdependent Hadoop jobs who need reliable orchestration replacing fragile cron-based scheduling.
The workflow covers directed acyclic graph design for your job dependencies, Oozie workflow.xml or Airflow DAG definition, action node configuration for each job type (Spark, Hive, Sqoop, shell), decision nodes for conditional branching, fork/join nodes for parallel execution, error handler and kill node configuration, SLA definition, and email or Slack alerting on failure. A coordinator job for time-triggered execution is included for Oozie.
Designed for data engineering teams running multiple interdependent Hadoop jobs who need reliable orchestration replacing fragile cron-based scheduling.
What the Freelancer needs to start the work
Please describe your job pipeline (each step, its dependencies, and its expected runtime), your orchestration platform preference (Oozie or Airflow), your Hadoop distribution, your trigger schedule, and your alerting channel.