Key Responsibilities:
Develop scalable and effective data-driven applications using Hadoop, Spark, Hive, Impala, and NiFi in an on-premises environment.
Design and implement high-performance Spark jobs using Java.
Build data pipelines and compute tiers leveraging Hadoop, Spark, and Impala.
Review and enhance code quality for Hadoop and Spark-based batch jobs.
Collaborate with cross-functional teams to deliver robust software solutions that meet business needs.
Mentor junior engineers and serve as a technical point of contact for Hadoop ecosystem technologies.
Evaluate and recommend recent tools and technologies to improve performance, scalability, and system reliability.
Ensure solutions follow best practices, are maintainable, scalable, and performance-optimized.
Required Skills:
Strong Java development experience, especially within the context of SpringBoot.
Experience in full stack software development with a data-intensive focus.
Expertise in big data technologies such as Hadoop, NiFi, Hive, Impala, and Spark.
Deep understanding of SQL (preferably Oracle).
Solid knowledge of object-oriented programming (OOP) principles.
Familiarity with Hadoop internals is a robust plus.
Strong analytical and problem-solving skills.
Excellent communication skills—both verbal and written.
Ability to mentor junior developers and lead technical improvements.
Required Skills for Big Data Engineer Job
Hadoop
NiFi
Hive and Spark
Java
Our Hiring Process
Screening (HR Round)
Technical Round 1
Technical Round 2
Final HR Round
📌 Big Data Engineer Pune (India)
🏢 Phygital Insights
📍 India
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