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Job Description
Structured overview of role & requirementsAbout This Role
Develop, maintain, and optimize scalable data pipelines and streaming data solutions using Databricks with cloud-native technologies on AWS and Azure.
Design and implement batch and real-time data ingestion frameworks integrating with event-streaming platforms such as AWS MSK and Confluent Kafka.
Collaborate with business, technology, and architecture teams to translate data requirements into scalable cloud-based data platforms and support cloud modernization initiatives.
Minimum Requirements
Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
2 to 5 years of experience in Data Engineering or related technical roles.
Hands-on experience with Databricks development and administration, PySpark, Spark SQL, and cloud platforms (AWS and/or Azure).
Working knowledge of Apache Kafka, AWS MSK or Confluent Kafka, and strong SQL skills.
Ideal Candidate Profile
Demonstrated ability working on cloud-native, event-driven architectures leveraging Databricks and streaming frameworks in a strategic transformation environment.
Experience collaborating across multiple technical and business teams to deliver scalable data platform solutions.
Familiarity with data lakes, distributed computing, and large-scale data processing in financial services or complex regulated industries preferred but not mandatory.