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Tier-1 brand, mid-level generalist data role, and metro location increases candidate competition.
Big Data and PySpark skills are broadly transferable across industries.
Explicit Big Data tech requirements and a minimum experience filter create moderate hiring rigidity.
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Participate in analysis, design, development, testing, and implementation of application systems supporting big data processing using technologies like Hadoop ecosystem and Spark.
Analyze complex problems, recommend and develop solutions, and support users and operations for applications with a focus on performance tuning and troubleshooting in Big Data domain.
Serve as a subject matter expert, advising stakeholders and coaching junior analysts, while ensuring compliance with laws, policies, and risk management requirements.
Minimum 2 years experience in Big Data technologies such as HDFS, Map Reduce, YARN, Apache Spark, Hive.
Strong knowledge of relevant data formats (Avro, Parquet, CSV, JSON) and programming skills in Python/Scala.
Bachelor’s degree or equivalent experience.
Work Experience Required: Minimum 2 years in Big Data domain.
Experienced in application development lifecycle including design, unit testing, and performance tuning in big data environments.
Familiar with UNIX/Linux environments and shell scripting, with exposure to Agile/Scrum, SCM tools (GIT, JIRA), and real-time data processing (Kafka) as plus.
Able to translate functional requirements into scalable, performant applications, collaborate effectively with global teams, and propose best practices and standards.