Python, Spark Scala Developer

Responsibilities :

Data Engineering & Development

Design, develop, and maintain scalable batch/stream data pipelines using Spark with Scala and Python.

Implement efficient transformations, joins, aggregations, and data quality checks for large datasets.

Build reusable frameworks/utilities to standardize pipeline patterns and reduce delivery time. Performance & Reliability

Tune Spark jobs (partitioning, caching, shuffles, memory/executor settings) to improve performance and cost efficiency.

Troubleshoot production issues, perform root-cause analysis, and implement preventive fixes.

Ensure reliability through robust logging, monitoring hooks, and failure-handling strategies. Collaboration & Delivery

Work with stakeholders to refine requirements and deliver well-documented, production-ready solutions.

Conduct code reviews, enforce best practices, and mentor team members on Spark/Scala/Python patterns.

Contribute to CI/CD-friendly development practices including testing, version control, and release readiness.

Additional Responsibilities:

Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).

5-9 years of experience in data engineering or backend development with strong hands-on delivery ownership.

Strong proficiency in Python and Apache Spark for large-scale data processing.

Solid experience with Scala for Spark-based development and production-grade implementations.

Working knowledge of Hive and SQL-based data querying/processing concepts.

Technical and Professional Requirements:

Technology- Analytics - Packages- Python - Big Data,Technology- Big Data - Data Processing- Spark,Technology- Big Data - Data Processing- Scala