Description

You will design and deliver big data pipelines for structured and unstructured data across multiple geographies within the healthcare domain.

Responsibilities

• Design and build cloud migration strategies for cloud and on-premise data architectures, applications, and pipelines.
• Develop utilities for migration, storage, and processing to solve big data problems at massive scale.
• Build ingestion tools and processing jobs capable of handling terabytes or petabytes of data per day.
• Design next-gen storage and compute solutions for large-scale healthcare and life sciences customers.
• Create advanced tooling for automation, testing, monitoring, and data operations across multiple cloud clusters.

Required Skills

• 12+ years of hands-on experience in data architectures, cloud, data structures, and distributed systems.
• Expertise in Hadoop, Spark, and distributed processing frameworks like MapReduce, Storm, or Flink.
• Strong software development skills in Python, PySpark, Java, C/C++, Scala, or SQL.
• Proven experience building and deploying large-scale enterprise big data solutions using Databricks or Snowflake.
• Deep knowledge of RDBMS and NoSQL databases, including Hive and HBase.
• Experience with cloud platforms such as AWS, GCP, or Azure and big data distributions like EMR or Google DataProc.
• Proficiency in designing and developing ETL/ELT pipelines.
• Experience with orchestration frameworks such as Airflow, Oozie, Apache NiFi, or Google DataFlow.
• Familiarity with messaging or event solutions like Kafka, Kinesis, or Cloud pub-sub.

Preferred Skills

• Hands-on experience with Kubernetes, Swarm, or Terraform.
• Exposure to DevOps, DevSecOps, or Machine Learning and AI initiatives.

Key Skills

Education

ANY GRADUATE