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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain high-performance, fault-tolerant data pipelines using modern big data technologies like Apache Spark.
Implement and optimize ETL/ELT data processing solutions within Google Cloud Platform services such as Airflow, Dataproc, and BigQuery for performance and cost efficiency.
Collaborate with data scientists and engineers, ensure data quality, participate in code reviews, and mentor junior team members.
Minimum Requirements
Strong proficiency in Java and/or Scala for big data application development.
Extensive experience with Apache Spark and hands-on experience with Google Cloud Platform services: Airflow, Dataproc, BigQuery.
Proficiency in Python and experience with frontend frameworks like Angular/React/Node JS and relational databases such as Oracle.
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced in financial services domain with solid understanding of data warehousing, ETL/ELT, and data modeling concepts.
Familiar with CI/CD pipelines, DevOps practices, version control systems (Git/Github), and SDLC tooling such as JIRA, TeamCity, Terraform.
Comfortable working in collaborative settings involving code reviews, mentoring, and staying updated on big data technologies.