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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain high-performance, fault-tolerant data pipelines using big data technologies including Apache Spark on GCP.
Implement ETL solutions, optimize data processing jobs for performance and cost efficiency, ensuring data quality, integrity, and security.
Provide engineering thought leadership, participate in code reviews, mentor junior engineers, and collaborate with data scientists, analysts, and engineers.
Minimum Requirements
Strong proficiency in Java and/or Scala for big data application development.
Extensive experience with Apache Spark and Google Cloud Platform services including Airflow, Dataproc, and BigQuery.
Solid understanding of data warehousing, ETL/ELT principles, data modeling, and version control systems (e.g., Git).
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced engineer with multiple implementations demonstrating depth in big data engineering and architectural patterns.
Comfortable providing technical leadership and mentoring within teams, with strong collaboration skills.
Familiar with cloud-based big data ecosystems (especially GCP) and capable of leveraging emerging technologies including AI tools responsibly.