Job Description & Details
This is a heavy-duty migration gig where you are coming in to rip out legacy on-prem Cloudera Hadoop workflows and rebuild them natively in AWS. If you enjoy untangling massive big data pipelines and orchestrating cloud transformations without hand-holding, this 6-month contract will keep you thoroughly occupied.
What You'll Actually Be Doing
Your day-to-day will revolve around evaluating existing HDFS, Hive, Spark, and Oozie pipelines and mapping out their cloud equivalents using modern AWS tools. You will be writing infrastructure code, debugging messy legacy scripts, and coordinating directly with QA, DevOps, and Product teams to ensure the healthcare datasets transition smoothly without data loss or downtime. Expect to spend a solid chunk of your time reviewing code, writing operational runbooks, and mentoring engineers who are less familiar with cloud-native patterns.
The Core Tech Stack
You need deep, battle-tested experience with the Cloudera Hadoop ecosystem and AWS big data services like Amazon EMR, AWS Glue, and Apache Airflow. Terraform is non-negotiable for the infrastructure side, alongside solid Python and Bash scripting capabilities. Familiarity with deployment tools like Bitbucket, Gradle, and Octopus Deploy will be expected from day one because you are driving the actual execution, not just drawing architecture diagrams.
Interview Expectations
They are going to test your real-world battle scars by asking you to walk through a previous cloud migration failure and how you remediated data consistency issues. The interviewer wants to see if you can methodically design a multi-terabyte data migration strategy from HDFS to S3/EMR while minimizing pipeline downtime. They are looking for architectural pragmatism over textbook answers.
Application Advice
Skip the generic fluff on your resume and highlight specific AWS migration projects where you took ownership of moving big data workloads from on-prem to the cloud. Make sure keywords like Amazon EMR, AWS Glue, Apache Airflow, Terraform, and Cloudera are explicitly visible so you easily clear the ATS filters.