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Metro location, broad generalist data-engineer skills, and attractive mid-senior level increase candidate competition.
Core big-data, Spark, Kafka, and AWS skills are broadly transferable across industries.
Explicit 7-8 years plus many mandatory technologies creates high shortlisting strictness.
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Lead design, architecture, and implementation of high-throughput data ingestion systems and ETL pipelines.
Mentor and guide engineering team to ensure technical excellence and best practices.
Own full software development lifecycle including system design, deployment, and infrastructure management.
7 to 8 years of professional software engineering experience with 1–2 years in leadership or architectural role.
Expert-level proficiency in Java and Python.
Strong experience in Apache Spark, ETL pipeline design, SQL and NoSQL databases, and message queue systems (Kafka, AWS SQS, RabbitMQ).
Extensive experience with AWS cloud services, DevOps CI/CD tools (GitLab or Jenkins), containerization (Kubernetes, Docker), and Infrastructure as Code (Terraform, CloudFormation).
Experienced in leading high-volume data ingestion or streaming platform projects at scale.
Skilled in Agile/Scrum environments with ability to drive technical delivery and sprint planning.
Strong problem solver with deep system design, data structures, algorithms capabilities and good communication skills for cross-functional collaboration.