Scala/Spark Developer

Job Title : Scala/Spark Developer

Job Location : Bengaluru

Exp Range : 5-10 years

Notice Period : immediate

Position Overview : We are seeking a Senior Data Engineer with deep expertise in Scala-based Spark development and end-to-end deployment of data pipelines . The ideal candidate should have a strong software engineering foundation, excellent understanding of distributed systems, proficient in software design, modern project/code structuring skills, with good understanding on CI/CD processes and implementation which enables them to deliver reliable, scalable and robust data solutions.

Skills Required :

Languages: Scala, Java

• Big Data Orchestration: Airflow, Spark on Kubernetes, Yarn, Oozie

• Big Data Processing: Hadoop, Kafka, Spark & Spark Structured Streaming.

• Experience on SOLID & DRY principles with Good Software Architecture & Design implementation experience

• Advanced Scala experience (e.g. Functional Programming, using Case classes, Complex Data Structures & Algorithms)

• Proficient in developing automated frameworks for unit & integration testing.

• Experience with Docker and Helm and related container technologies.

• Proficient in deploying and managing Spark workloads on Kubernetes clusters.

• Experience in evaluation and implementation of Data Validation & Data Quality

Roles & Responsibilities :

Design & implement robust, scalable, batch & real-time data engineering solutions using Apache Spark (Scala) & Spark structure streaming.

• Architect well-structured Scala projects using reusable, modular, and testable codebases aligned with SOLID principles and clean architecture principles & practices.

• Develop, Deploy & Manage Spark jobs on Kubernetes clusters, ensuring efficient resource utilization, fault tolerance, and scalability.

• Orchestrate data workflows using Apache Airflow — manage DAGs, task dependencies, retries, and SLA alerts.

• Write and maintain comprehensive unit tests and integration tests for Pipelines / Utilities developed.

• Work on performance tuning, partitioning strategies, and data quality validation. • Use and enforce version control best practices (branching, PRs, code review) and continuous integration (CI/CD) for automated testing and deployment.

• Write clear, maintainable documentation (README, inline docs, docstrings).

• Participate in design reviews and provide technical guidance to peers and junior engineers.