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Mid-level data role at a well-known multinational with hybrid metro hiring attracts many qualified applicants.
Core data engineering skills (AWS, Databricks, Spark) are transferable across industries despite healthcare context.
Explicit 5–8 years requirement plus mandatory AWS, Databricks, Spark and CI/CD restrict candidate pool.
Own design and implementation of scalable, cloud-based data engineering solutions using AWS services, Databricks, and Teradata Vantage replacing manual workflows.
Lead deployment and operational processes with DevOps tools like Github, Jenkins, Terraform, and Liquibase ensuring adherence to enterprise architecture standards.
Collaborate in agile teams to deliver advanced, user-centric analytical and reporting capabilities with accountability for code quality and production releases.
5 to 8 years of experience in application program development or equivalent in education and work experience.
Bachelor’s degree in Engineering, Computer Science, or related discipline.
Extensive hands-on experience with AWS services: Lambda, Step Functions, CloudTrail, CloudWatch, SNS, SQS, S3, VPC, EC2, RDS, and IAM.
Proficient in Python, Databricks, SQL, Unix, and working knowledge of Spark and real-time analytic frameworks.
Experienced in business intelligence or analytics development on large-scale projects with documented technical delivery.
Skilled in SDLC processes including build, test, deploy and capable of building web services (HTTP API/RPC).
Strong operating style centered on technical excellence, ownership, automation, and collaborative agile team delivery.